{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.8.0\n",
      "1.14.0\n",
      "0.22.0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/envs/py2env/lib/python2.7/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n"
     ]
    }
   ],
   "source": [
    "# Import libraries and modules\n",
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import shutil\n",
    "print tf.__version__\n",
    "print np.__version__\n",
    "print pd.__version__\n",
    "np.set_printoptions(threshold=np.inf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# change these to try this notebook out\n",
    "BUCKET = 'youtube8m-4-train'\n",
    "PROJECT = 'qwiklabs-gcp-8d3d0cd07cef9252'\n",
    "REGION = 'us-central1'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Import os environment variables\n",
    "import os\n",
    "os.environ['BUCKET'] = BUCKET\n",
    "os.environ['PROJECT'] = PROJECT\n",
    "os.environ['REGION'] = REGION"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Local Development"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Set logging verbosity to INFO for richer output\n",
    "tf.logging.set_verbosity(tf.logging.INFO)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# The number of video classes\n",
    "NUM_CLASSES = 4716"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "arguments = {}\n",
    "arguments[\"train_file_pattern\"] = \"gs://youtube-8m-team/1/video_level/train/train*.tfrecord\"\n",
    "arguments[\"eval_file_pattern\"] = \"gs://youtube-8m-team/1/video_level/validate/validate-0.tfrecord\"\n",
    "arguments[\"output_dir\"] = \"trained_model\"\n",
    "arguments[\"batch_size\"] = 10\n",
    "arguments[\"train_steps\"] = 100\n",
    "arguments[\"hidden_units\"] = [1024, 256, 64]\n",
    "arguments[\"top_k\"] = 5\n",
    "arguments[\"start_delay_secs\"] = 60\n",
    "arguments[\"throttle_secs\"] = 30"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Create an input function to read our training and validation data\n",
    "# Then provide the results to the Estimator API\n",
    "def read_dataset_video(file_pattern, mode, batch_size):\n",
    "  def _input_fn():\n",
    "    print(\"\\nread_dataset_video: _input_fn: file_pattern = {}\".format(file_pattern))\n",
    "    print(\"read_dataset_video: _input_fn: mode = {}\".format(mode))\n",
    "    print(\"read_dataset_video: _input_fn: batch_size = {}\".format(batch_size))\n",
    "\n",
    "    # This function will decode frame examples from the frame level TF Records\n",
    "    def decode_example(serialized_examples):\n",
    "      # Create feature map\n",
    "      feature_map = {\n",
    "          'video_id': tf.FixedLenFeature(shape = [], dtype = tf.string),\n",
    "          'labels': tf.VarLenFeature(dtype = tf.int64),\n",
    "          'mean_rgb': tf.FixedLenFeature(shape = [1024], dtype = tf.float32),\n",
    "          'mean_audio': tf.FixedLenFeature(shape = [128], dtype = tf.float32)\n",
    "      }\n",
    "\n",
    "      # Parse TF Records into our features\n",
    "      features = tf.parse_single_example(serialized = serialized_examples, features = feature_map)\n",
    "      print(\"\\nread_dataset_video: _input_fn: decode_example: features = {}\".format(features)) # shape = video_id = (), mean_rgb = (1024,), mean_audio = (128,), labels = SparseTensor object\n",
    "\n",
    "      # Extract and format labels\n",
    "      sparse_labels = features.pop(\"labels\") # SparseTensor object\n",
    "      print(\"read_dataset_video: _input_fn: decode_example: sparse_labels = {}\\n\".format(sparse_labels))\n",
    "      labels = tf.cast(x = tf.sparse_to_dense(sparse_indices = sparse_labels.values, output_shape = (NUM_CLASSES,), sparse_values = 1, validate_indices = False), dtype = tf.float32)\n",
    "      print(\"read_dataset_video: _input_fn: decode_example: labels = {}\\n\".format(labels)) # shape = (NUM_CLASSES,)\n",
    "\n",
    "      return features, labels\n",
    "\n",
    "    # Create list of files from file pattern\n",
    "    file_list = tf.gfile.Glob(filename = file_pattern)\n",
    "    #print(\"read_dataset_video: _input_fn: file_list = {}\".format(file_list))\n",
    "\n",
    "    # Create dataset from file list\n",
    "    dataset = tf.data.TFRecordDataset(filenames = file_list)\n",
    "    print(\"read_dataset_video: _input_fn: dataset.TFRecordDataset = {}\".format(dataset))\n",
    "\n",
    "    # Decode TF Record dataset examples\n",
    "    dataset = dataset.map(map_func = lambda x: decode_example(serialized_examples = x))\n",
    "    print(\"read_dataset_video: _input_fn: dataset.map = {}\".format(dataset))\n",
    "\n",
    "    # Determine amount of times to repeat file and if we should shuffle based on if we are training or evaluating\n",
    "    if mode == tf.estimator.ModeKeys.TRAIN:\n",
    "      num_epochs = None # read files forever\n",
    "      \n",
    "      # Shuffle the dataset within a buffer\n",
    "      dataset = dataset.shuffle(buffer_size = batch_size * 10, seed = None)\n",
    "      print(\"read_dataset_video: _input_fn: dataset.shuffle = {}\".format(dataset))\n",
    "    else:\n",
    "      num_epochs = 1 # read files only once\n",
    "\n",
    "    # Repeat files num_epoch times\n",
    "    dataset = dataset.repeat(count = num_epochs)\n",
    "    print(\"read_dataset_video: _input_fn: dataset.repeat = {}\".format(dataset))\n",
    "\n",
    "    # Group the data into batches\n",
    "    dataset = dataset.batch(batch_size = batch_size)\n",
    "    print(\"read_dataset_video: _input_fn: dataset.batch = {}\".format(dataset))\n",
    "\n",
    "    # Create a iterator and then pull the next batch of features and labels from the example queue\n",
    "    batch_features, batch_labels = dataset.make_one_shot_iterator().get_next()\n",
    "    print(\"read_dataset_video: _input_fn: batch_features = {}\".format(batch_features))\n",
    "    print(\"read_dataset_video: _input_fn: batch_labels = {}\\n\".format(batch_labels))\n",
    "\n",
    "    return batch_features, batch_labels\n",
    "  return _input_fn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def try_input_function():\n",
    "  with tf.Session() as sess:\n",
    "    fn = read_dataset_video(file_pattern = \"gs://youtube-8m-team/1/video_level/train/train*.tfrecord\", mode = tf.estimator.ModeKeys.TRAIN, batch_size = 5)\n",
    "    batch_features, batch_labels = fn()\n",
    "    features, labels = sess.run([batch_features, batch_labels])\n",
    "    \n",
    "    print(\"\\ntry_input_function: features = {}\".format(features))\n",
    "    print(\"try_input_function: labels = {}\\n\".format(labels))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "read_dataset_video: _input_fn: file_pattern = gs://youtube-8m-team/1/video_level/train/train*.tfrecord\n",
      "read_dataset_video: _input_fn: mode = train\n",
      "read_dataset_video: _input_fn: batch_size = 5\n",
      "read_dataset_video: _input_fn: dataset.TFRecordDataset = <TFRecordDataset shapes: (), types: tf.string>\n",
      "\n",
      "read_dataset_video: _input_fn: decode_example: features = {'labels': <tensorflow.python.framework.sparse_tensor.SparseTensor object at 0x7f2b7c7b0fd0>, 'video_id': <tf.Tensor 'ParseSingleExample/ParseSingleExample:5' shape=() dtype=string>, 'mean_audio': <tf.Tensor 'ParseSingleExample/ParseSingleExample:3' shape=(128,) dtype=float32>, 'mean_rgb': <tf.Tensor 'ParseSingleExample/ParseSingleExample:4' shape=(1024,) dtype=float32>}\n",
      "read_dataset_video: _input_fn: decode_example: sparse_labels = SparseTensor(indices=Tensor(\"ParseSingleExample/ParseSingleExample:0\", shape=(?, 1), dtype=int64), values=Tensor(\"ParseSingleExample/ParseSingleExample:1\", shape=(?,), dtype=int64), dense_shape=Tensor(\"ParseSingleExample/ParseSingleExample:2\", shape=(1,), dtype=int64))\n",
      "\n",
      "read_dataset_video: _input_fn: decode_example: labels = Tensor(\"Cast:0\", shape=(4716,), dtype=float32)\n",
      "\n",
      "read_dataset_video: _input_fn: dataset.map = <MapDataset shapes: ({video_id: (), mean_audio: (128,), mean_rgb: (1024,)}, (4716,)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: dataset.shuffle = <ShuffleDataset shapes: ({video_id: (), mean_audio: (128,), mean_rgb: (1024,)}, (4716,)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: dataset.repeat = <RepeatDataset shapes: ({video_id: (), mean_audio: (128,), mean_rgb: (1024,)}, (4716,)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: dataset.batch = <BatchDataset shapes: ({video_id: (?,), mean_audio: (?, 128), mean_rgb: (?, 1024)}, (?, 4716)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: batch_features = {'video_id': <tf.Tensor 'IteratorGetNext:2' shape=(?,) dtype=string>, 'mean_audio': <tf.Tensor 'IteratorGetNext:0' shape=(?, 128) dtype=float32>, 'mean_rgb': <tf.Tensor 'IteratorGetNext:1' shape=(?, 1024) dtype=float32>}\n",
      "read_dataset_video: _input_fn: batch_labels = Tensor(\"IteratorGetNext:3\", shape=(?, 4716), dtype=float32)\n",
      "\n",
      "\n",
      "try_input_function: features = {'video_id': array(['--sJx5wtvm4', '--poIkLjlMM', '--f5fEIOW1Q', '--CjIdX9c1k',\n",
      "       '--hoQ2sGG4M'], dtype=object), 'mean_audio': array([[ 9.49755609e-01, -1.25520840e-01, -1.22143710e+00,\n",
      "         4.18073446e-01,  5.38727999e-01,  7.85580456e-01,\n",
      "        -1.02470994e+00, -1.19655132e+00,  1.14011383e+00,\n",
      "         4.32344407e-01,  1.57201707e+00,  5.74070737e-02,\n",
      "        -2.36857995e-01,  4.19488758e-01,  8.57131332e-02,\n",
      "        -1.02081788e+00,  1.10378778e+00,  1.33636916e+00,\n",
      "        -4.69439447e-01, -2.14920804e-01,  1.71826506e+00,\n",
      "        -2.55610764e-01, -3.94664288e-01, -1.16081500e+00,\n",
      "        -3.54132131e-02,  7.35455155e-01,  6.77545667e-01,\n",
      "        -7.55448580e-01,  2.02121809e-01, -5.44804335e-01,\n",
      "         1.59898594e-01,  2.24648714e-01, -8.15284997e-02,\n",
      "        -9.26110566e-01,  1.35602564e-01,  9.42679107e-01,\n",
      "        -1.02875985e-01,  5.04171014e-01,  2.19695151e-01,\n",
      "        -2.31786504e-01,  6.74321353e-02,  3.37637067e-01,\n",
      "         1.09635735e+00, -4.70894612e-02,  6.44168079e-01,\n",
      "        -4.37870882e-02, -3.08134761e-02,  1.43976435e-01,\n",
      "         5.34128308e-01,  6.84936121e-02,  1.05637503e+00,\n",
      "        -1.68451697e-01,  8.84258002e-02,  2.16274828e-01,\n",
      "         5.03463387e-01,  4.49445993e-01, -3.51497531e-01,\n",
      "        -3.40764821e-01,  7.40368813e-02, -5.59547067e-01,\n",
      "         1.48576170e-01, -3.06089908e-01,  1.60488307e-01,\n",
      "        -2.96418667e-01, -3.77562702e-01,  2.34437883e-01,\n",
      "        -4.95150805e-01,  7.92892873e-01, -7.17589259e-01,\n",
      "         1.94573522e-01, -5.91273427e-01,  4.84828562e-01,\n",
      "        -6.34793997e-01,  5.78474462e-01,  4.86479759e-01,\n",
      "        -2.59620786e-01, -1.26228482e-01,  3.42590630e-01,\n",
      "         2.13915989e-01,  3.91260795e-02, -2.76604414e-01,\n",
      "         3.96254182e-01,  2.11439207e-01, -8.96664932e-02,\n",
      "         7.95369625e-01,  4.74331737e-01,  5.39867580e-02,\n",
      "         6.51126683e-01, -1.88501820e-01,  1.13901250e-01,\n",
      "        -5.10247350e-01, -6.69586897e-01, -8.61950159e-01,\n",
      "        -5.69572151e-01,  9.58561376e-02, -1.94516852e-01,\n",
      "        -1.26504218e-02,  3.85049701e-01, -9.66250673e-02,\n",
      "         1.19680405e-01,  1.06569254e+00,  8.18014503e-01,\n",
      "        -8.68201077e-01,  7.27199197e-01, -3.27005461e-02,\n",
      "        -8.28454614e-01, -7.46249139e-01, -1.42976239e-01,\n",
      "         2.81732589e-01, -8.58175993e-01,  5.46040416e-01,\n",
      "        -5.94929636e-01,  1.41381711e-01,  6.17985010e-01,\n",
      "        -5.92806697e-01, -2.10674897e-01, -1.79538235e-01,\n",
      "         9.20819938e-02, -8.41232240e-02, -2.52544284e-01,\n",
      "         8.88661683e-01,  3.24427575e-01, -8.35059404e-01,\n",
      "         5.25282621e-01, -4.69715185e-02, -7.96728253e-01,\n",
      "         3.25489044e-01, -1.03229813e-01],\n",
      "       [-8.91931772e-01, -1.31051660e+00,  7.49585748e-01,\n",
      "        -4.44466658e-02,  2.43512895e-02, -7.36026764e-02,\n",
      "        -7.41292357e-01,  1.40358591e-02, -3.84259105e-01,\n",
      "         9.25374329e-01, -7.23219037e-01, -1.38681662e+00,\n",
      "         3.77462983e-01, -7.55870342e-01,  6.66039288e-01,\n",
      "         6.17786944e-01,  1.43618122e-01,  5.48477471e-01,\n",
      "        -3.19126964e-01,  1.56150103e-01, -1.89715207e-01,\n",
      "        -1.60388693e-01,  1.19246721e+00, -9.71556664e-01,\n",
      "        -7.70618856e-01, -1.17251441e-01, -3.19297463e-01,\n",
      "        -1.24242060e-01,  1.33302703e-01,  5.38758814e-01,\n",
      "         1.70387089e-01, -3.18956465e-01, -1.04674840e+00,\n",
      "         8.99372578e-01, -8.37541282e-01,  2.95792043e-01,\n",
      "         2.01333389e-01, -5.28589904e-01,  2.89739192e-01,\n",
      "        -2.86305159e-01,  6.64590001e-01, -5.23901045e-01,\n",
      "         1.26493096e+00,  4.74990666e-01, -2.59470902e-02,\n",
      "         1.24351293e-01, -2.21343517e-01,  8.99287343e-01,\n",
      "         4.28443372e-01, -2.44617164e-01,  7.44811654e-01,\n",
      "        -4.68317091e-01,  4.14973617e-01,  5.94683766e-01,\n",
      "        -3.25861841e-01, -1.06729412e+00, -2.76671737e-01,\n",
      "         5.08665025e-01,  3.13353837e-01,  5.89568675e-01,\n",
      "        -5.49476504e-01, -6.02161944e-01, -2.97814101e-01,\n",
      "        -2.83321351e-01,  1.25865834e-02, -1.78888261e-01,\n",
      "         6.70728087e-01, -4.68658090e-01,  2.28784367e-01,\n",
      "         8.22305262e-01, -6.38564289e-01, -8.51778269e-01,\n",
      "         1.31682917e-01,  4.56320614e-01,  1.22731514e-01,\n",
      "        -5.13520353e-02, -6.47365227e-02,  5.27846575e-01,\n",
      "        -2.00542152e-01, -1.51201515e-02,  3.24010283e-01,\n",
      "         4.70642835e-01,  1.24266036e-01,  4.95962530e-01,\n",
      "         4.94939536e-01, -5.78547239e-01, -2.72664905e-01,\n",
      "         6.47113442e-01,  1.83856830e-01, -6.92548454e-02,\n",
      "         2.60412663e-01, -2.02352405e-02,  2.51290768e-01,\n",
      "        -2.08555788e-01, -8.46853703e-02,  9.76951480e-01,\n",
      "        -9.01479900e-01, -3.77694756e-01, -6.42059624e-01,\n",
      "        -5.23133814e-01,  9.27590847e-01, -4.15481143e-02,\n",
      "        -1.01861548e+00, -7.90311992e-01, -3.50329012e-01,\n",
      "        -5.91675997e-01,  3.23413521e-01,  5.62373459e-01,\n",
      "         1.34922475e-01,  8.25459540e-01,  3.84027332e-01,\n",
      "        -1.59365669e-01,  2.63225973e-01,  1.46772429e-01,\n",
      "         1.00713050e+00, -3.21173012e-01,  3.54359806e-01,\n",
      "         2.75331676e-01,  5.73285639e-01, -5.91420233e-01,\n",
      "        -4.08811539e-01,  4.41401601e-01, -5.77353716e-01,\n",
      "        -2.20490992e-01, -2.69595861e-01, -1.65759534e-01,\n",
      "         7.61841983e-02,  5.10881543e-01],\n",
      "       [ 1.02048063e+00, -8.83800268e-01, -4.98870581e-01,\n",
      "         1.74571559e-01,  1.51411727e-01,  9.50426221e-01,\n",
      "        -8.55249390e-02, -1.22646384e-01,  5.48302606e-02,\n",
      "        -8.93162787e-01,  7.78123558e-01, -1.15284305e-02,\n",
      "         1.21232951e+00, -3.55230302e-01, -2.40498766e-01,\n",
      "         1.01642706e-01, -7.63566196e-01,  3.81285459e-01,\n",
      "        -1.80299610e-01,  8.71830583e-01, -1.53279796e-01,\n",
      "         5.82004070e-01,  7.89756253e-02,  5.23693800e-01,\n",
      "        -6.77907646e-01,  3.11776567e-02,  1.39503285e-01,\n",
      "         1.68165654e-01,  3.64860028e-01, -3.07760864e-01,\n",
      "        -2.51093149e-01,  5.19505322e-01, -1.51555121e-01,\n",
      "        -5.49050272e-01, -3.71245086e-01, -5.39605618e-01,\n",
      "        -5.51379174e-02, -3.10746785e-02,  2.70906627e-01,\n",
      "        -1.75530615e-03, -2.44687244e-01,  3.85391802e-01,\n",
      "         5.92187822e-01,  1.95021212e-01,  1.10348172e-01,\n",
      "        -5.66983297e-02, -1.15829833e-01,  2.47746795e-01,\n",
      "        -2.96837956e-01, -1.69048190e-01, -1.34308428e-01,\n",
      "        -2.75895536e-01, -9.34912711e-02, -3.14577401e-01,\n",
      "         4.28397059e-02, -3.31278555e-02, -2.24513337e-02,\n",
      "        -6.89352676e-02, -2.16189146e-01,  5.05596511e-02,\n",
      "         8.29945743e-01,  5.66235662e-01, -4.12390769e-01,\n",
      "         1.93625048e-01, -8.36360157e-02, -3.71162951e-01,\n",
      "         4.80494976e-01, -2.99630255e-01, -5.51103413e-01,\n",
      "         7.14199319e-02,  2.86428660e-01,  4.49533075e-01,\n",
      "         1.51740223e-01, -5.36484778e-01, -5.84693432e-01,\n",
      "         1.16425581e-01,  7.44205058e-01,  4.88050669e-01,\n",
      "        -1.58043161e-01, -6.42182350e-01, -2.17338920e-01,\n",
      "        -2.66122401e-01,  1.21405411e+00, -5.57098687e-01,\n",
      "         6.92846254e-02,  5.15481114e-01, -2.67190069e-01,\n",
      "         4.62262750e-01,  5.08171797e-01, -5.94906509e-02,\n",
      "         7.29586422e-01,  9.87465501e-01,  4.93553191e-01,\n",
      "         3.75290185e-01, -6.99178576e-01, -3.12524229e-01,\n",
      "        -2.45180011e-01, -4.57150042e-01,  5.81100643e-01,\n",
      "        -2.20952511e-01, -3.07678729e-01,  2.26892135e-03,\n",
      "        -7.50672281e-01, -2.89692879e-01,  5.93994617e-01,\n",
      "         8.08099926e-01, -4.92464691e-01, -3.27389210e-01,\n",
      "         7.65118152e-02,  6.91890121e-01,  2.23601431e-01,\n",
      "         3.52458835e-01,  8.60385522e-02, -6.89076960e-01,\n",
      "         3.26670945e-01,  6.72015369e-01,  4.95442092e-01,\n",
      "        -1.01616234e-03, -8.26504901e-02,  2.90535003e-01,\n",
      "         2.32471153e-01, -1.26916990e-01, -2.36011129e-02,\n",
      "        -5.50857067e-01,  2.32224777e-01, -1.99353084e-01,\n",
      "        -6.09689392e-02,  8.71062055e-02],\n",
      "       [ 5.06636024e-01,  7.68858254e-01,  8.93564105e-01,\n",
      "        -9.61756110e-01, -6.72605813e-01, -1.76473653e+00,\n",
      "         4.07498777e-01,  1.62522423e+00,  2.38714457e-01,\n",
      "         3.37328851e-01,  1.61978638e+00, -1.15429327e-01,\n",
      "         3.21119696e-01, -1.07657969e+00, -7.92396665e-01,\n",
      "         1.14067519e+00,  1.10250533e+00,  3.72047782e-01,\n",
      "         1.02825689e+00,  1.15060985e+00, -4.11429316e-01,\n",
      "        -3.51560056e-01,  1.12817848e+00, -4.73651942e-03,\n",
      "         5.92649102e-01,  9.47211206e-01,  6.12570643e-01,\n",
      "        -1.34277570e+00,  1.06479168e-01,  3.89236100e-02,\n",
      "         6.19943202e-01, -2.08933819e-02,  1.39625692e+00,\n",
      "        -3.18984896e-01,  4.17747140e-01,  3.29628251e-02,\n",
      "         1.15568173e+00,  9.96518373e-01,  4.43368047e-01,\n",
      "        -8.10592711e-01, -7.25154817e-01,  3.76387656e-01,\n",
      "         2.46975899e-01, -9.24370527e-01,  4.57209982e-02,\n",
      "         2.99106628e-01, -5.92553496e-01,  2.97904015e-01,\n",
      "        -1.55877578e+00,  8.45302701e-01,  8.37668717e-01,\n",
      "         9.06949759e-01,  3.67394209e-01, -8.80553484e-01,\n",
      "         5.38688302e-01, -2.07403183e-01,  1.14553797e+00,\n",
      "         1.44178510e-01,  9.87995505e-01,  7.54636049e-01,\n",
      "         8.32910538e-01,  3.75707924e-01, -8.75011027e-01,\n",
      "        -3.55481625e-01, -4.93378267e-02,  1.74714054e-03,\n",
      "        -5.61913013e-01, -4.90749598e-01, -2.08030641e-01,\n",
      "        -6.43220186e-01, -9.84881520e-02, -8.60475063e-01,\n",
      "        -2.61221398e-02,  4.36817817e-02, -5.73363960e-01,\n",
      "         1.57947266e+00,  1.51446491e-01,  3.26086998e-01,\n",
      "        -1.12170386e+00, -4.00658101e-01, -7.80997932e-01,\n",
      "         8.37407291e-01,  2.94034719e-01,  4.79446501e-01,\n",
      "         1.59237340e-01,  3.16033512e-02, -4.62828010e-01,\n",
      "        -1.28599143e+00, -2.98279017e-01,  2.81276554e-01,\n",
      "        -1.22069851e-01, -5.73416233e-01, -1.57573119e-01,\n",
      "        -4.74017560e-01,  7.82034695e-01, -2.94984877e-01,\n",
      "         5.03760219e-01,  5.03080487e-01, -1.42357439e-01,\n",
      "         2.31446490e-01, -5.70906460e-01,  1.02098894e+00,\n",
      "        -5.88997960e-01,  5.45903981e-01, -5.64893365e-01,\n",
      "        -1.44640970e+00,  1.08891058e+00, -3.15220177e-01,\n",
      "        -3.61546963e-01, -3.60135198e-01,  3.79995495e-01,\n",
      "         8.42217743e-01, -2.08553508e-01, -5.94645023e-01,\n",
      "         1.74400732e-01, -7.07481623e-01,  1.44007355e-02,\n",
      "        -5.82880318e-01,  3.89982432e-01, -1.55167893e-01,\n",
      "         4.29145843e-01,  3.34857032e-02,  1.00744653e+00,\n",
      "         1.26449227e+00, -9.94854152e-01, -3.31586182e-01,\n",
      "        -9.24370527e-01, -1.88161358e-01],\n",
      "       [ 3.20221245e-01, -2.75674909e-02,  7.18732774e-01,\n",
      "        -1.34143615e+00, -6.66067541e-01, -6.62918866e-01,\n",
      "         7.69054830e-01,  1.27473676e+00,  6.85585499e-01,\n",
      "         9.30268466e-01,  1.54198647e-01,  3.65906090e-01,\n",
      "        -7.96069950e-02, -5.63477039e-01, -1.27352804e-01,\n",
      "        -3.39003026e-01, -6.47919595e-01, -1.17066181e+00,\n",
      "        -5.21398902e-01,  2.07096890e-01,  8.08098733e-01,\n",
      "        -1.15222752e+00, -4.86351885e-02,  1.62958889e-03,\n",
      "        -2.60056406e-01,  7.56975234e-01,  1.03772521e+00,\n",
      "         2.82952040e-01,  1.47007096e+00,  4.36666071e-01,\n",
      "        -9.73667383e-01, -1.20501137e+00, -6.59827411e-01,\n",
      "        -1.09623790e+00, -1.04625940e+00,  9.66632217e-02,\n",
      "         2.22897664e-01, -3.22228998e-01,  6.75795913e-01,\n",
      "         9.09887791e-01,  1.45444191e+00, -9.30100739e-01,\n",
      "        -1.20180535e+00, -2.39561200e-01, -1.14902163e+00,\n",
      "         9.46126521e-01,  6.44995868e-01, -3.52961309e-02,\n",
      "         7.82909095e-01, -4.07015026e-01,  1.21731591e+00,\n",
      "         2.93085158e-01,  5.42462587e-01, -6.98642373e-01,\n",
      "         1.12063251e-01, -9.20873135e-02, -6.09047353e-01,\n",
      "         6.17745221e-01,  5.67251444e-01, -1.02610767e+00,\n",
      "         1.34400833e+00, -3.87722075e-01, -1.09818435e+00,\n",
      "         5.02913892e-02, -9.35882926e-01,  1.00670666e-01,\n",
      "         1.29867747e-01, -6.08589411e-01,  1.28504280e-02,\n",
      "         8.96788239e-02, -2.85475045e-01,  9.85170424e-01,\n",
      "         1.55136478e+00,  1.46932673e+00, -1.67140990e-01,\n",
      "        -2.99558342e-01, -5.21856904e-01, -1.77674830e-01,\n",
      "         4.84021679e-02,  3.53826523e-01,  8.32544148e-01,\n",
      "        -1.01762421e-01,  8.91911566e-01,  7.05565453e-01,\n",
      "         6.71798959e-02,  4.05121803e-01,  1.15468526e+00,\n",
      "        -1.17037559e+00,  4.48860168e-01, -6.17806494e-01,\n",
      "         1.10029852e+00,  1.21725857e+00, -1.09658134e+00,\n",
      "         7.29953647e-01, -1.35975587e+00,  9.26833510e-01,\n",
      "        -4.49139923e-02, -9.62217569e-01,  9.11100507e-02,\n",
      "         1.00194442e+00, -1.08318508e+00,  8.59508514e-01,\n",
      "         7.94072688e-01, -8.79492521e-01,  5.96906543e-01,\n",
      "        -8.86648655e-01, -1.17432570e+00,  1.01872899e-01,\n",
      "        -5.70404172e-01, -1.09491065e-01, -1.41574550e+00,\n",
      "         5.81678271e-01,  7.30068147e-01, -7.89210558e-01,\n",
      "        -9.96910572e-01, -2.32405052e-01, -9.40520108e-01,\n",
      "         3.07282954e-01, -9.67942476e-01, -1.00664294e+00,\n",
      "         7.93328464e-01,  1.18303411e-01, -7.24976957e-01,\n",
      "         3.95503938e-01, -4.79091763e-01, -1.35940179e-01,\n",
      "        -2.55190223e-01, -5.64164042e-01]], dtype=float32), 'mean_rgb': array([[-7.75026977e-01,  6.55490518e-01, -4.68260020e-01,\n",
      "         2.49652401e-01, -6.00630715e-02,  3.54698785e-02,\n",
      "        -3.60932887e-01, -3.37108612e-01, -6.41910359e-02,\n",
      "         5.13134658e-01,  3.17351043e-01, -6.79651797e-02,\n",
      "         9.58561376e-02, -3.94310445e-01,  2.22289875e-01,\n",
      "        -1.67508155e-01, -8.38715613e-01,  1.99880913e-01,\n",
      "         1.28172219e-01,  3.94956827e-01,  3.16957384e-02,\n",
      "         6.01119280e-01, -5.97092472e-02,  7.78385997e-01,\n",
      "        -3.99853736e-01, -1.42622411e-01,  9.16883163e-03,\n",
      "        -2.92762458e-01, -9.46599059e-03, -5.80186903e-01,\n",
      "        -2.81204164e-01, -7.31152534e-01, -2.15628460e-01,\n",
      "        -6.40927017e-01,  8.54930282e-01, -5.33599854e-01,\n",
      "        -3.29796225e-01,  7.02627450e-02, -1.74702615e-01,\n",
      "        -3.56215209e-01, -1.66682556e-01, -2.98069865e-01,\n",
      "        -2.70471454e-01,  2.65810430e-01, -3.90536308e-01,\n",
      "         1.43390715e+00, -1.17029019e-01,  1.02476668e+00,\n",
      "        -2.35206813e-01, -5.22008166e-03,  8.76002014e-02,\n",
      "        -8.75985205e-01,  2.80907005e-01,  3.78680855e-01,\n",
      "        -6.76781356e-01,  1.71810731e-01, -7.72550166e-01,\n",
      "         1.73343971e-01, -4.45851058e-01, -9.09716606e-01,\n",
      "        -4.87484574e-01, -1.01578623e-01, -1.58780456e-01,\n",
      "         3.22658449e-01, -2.35088870e-01,  2.51775354e-01,\n",
      "        -3.85818630e-01,  4.93870229e-02,  2.21424419e-02,\n",
      "        -8.29438046e-02,  3.20771366e-01, -1.61611065e-01,\n",
      "         1.86553463e-01,  1.48300435e-02, -2.46883065e-01,\n",
      "         3.95546556e-01, -9.38966215e-01,  1.51052952e-01,\n",
      "         6.91698670e-01, -7.85169959e-01, -9.67862010e-01,\n",
      "         1.06588855e-01, -4.16837364e-01, -7.40234077e-01,\n",
      "         7.79289678e-02, -3.71901482e-01,  2.88651325e-02,\n",
      "        -9.51468050e-01,  6.45937204e-01,  1.07020773e-02,\n",
      "         6.20461762e-01, -5.38199604e-01, -2.14920804e-01,\n",
      "         3.20495628e-02, -1.65149316e-01,  2.82086432e-01,\n",
      "        -1.67272270e-01,  4.54517484e-01,  6.74833000e-01,\n",
      "        -5.80979092e-03, -2.91818917e-01,  8.49858820e-01,\n",
      "         3.45303297e-01,  2.53662407e-01, -5.78221753e-02,\n",
      "         2.70056337e-01, -3.38995695e-01,  6.30604804e-01,\n",
      "         3.32447618e-01, -1.06532186e-01,  2.42457941e-01,\n",
      "         7.46187866e-01,  1.13527822e+00,  1.13783307e-01,\n",
      "         2.94548403e-02, -2.33437687e-01, -2.01475427e-01,\n",
      "        -6.80791378e-01,  4.24678206e-01,  3.90946805e-01,\n",
      "        -2.63316836e-02, -9.61964905e-01, -3.91951621e-01,\n",
      "         3.00131530e-01,  3.71250510e-01,  5.12073159e-01,\n",
      "        -8.05455983e-01,  7.61992037e-01,  5.48635125e-01,\n",
      "         5.00160992e-01,  9.83329192e-02,  3.07679802e-01,\n",
      "        -9.99234557e-01,  5.29174745e-01, -1.12059677e+00,\n",
      "         3.75732303e-01, -1.74466729e-01,  4.66783464e-01,\n",
      "         4.36826199e-01,  4.73742038e-01,  7.23542988e-01,\n",
      "        -3.08920503e-01, -1.78122923e-01,  3.42000902e-01,\n",
      "         6.87688649e-01,  6.52424037e-01,  7.25312114e-01,\n",
      "         6.59028769e-01, -2.82619476e-01,  9.62257445e-01,\n",
      "        -4.52573746e-01,  5.76351523e-01,  5.42266309e-01,\n",
      "        -6.47649705e-01,  6.28010035e-01, -6.39629662e-01,\n",
      "         6.29503429e-02, -8.55385214e-02,  8.31341922e-01,\n",
      "        -1.22454345e-01, -2.17397586e-01,  9.74287510e-01,\n",
      "        -8.45949873e-02, -1.32401315e-02,  4.54949401e-02,\n",
      "         3.07915688e-01, -2.51522642e-02, -3.75085920e-01,\n",
      "        -5.85966051e-01, -6.65498748e-02,  5.54020628e-02,\n",
      "         1.39022872e-01,  6.86509252e-01,  2.53544480e-01,\n",
      "         4.92140979e-01, -2.46057466e-01,  3.84460002e-01,\n",
      "         5.41047007e-02,  8.26270401e-01,  5.74070737e-02,\n",
      "        -2.56790191e-01,  5.77648878e-01, -3.91361892e-01,\n",
      "        -4.73253429e-02, -4.67670321e-01, -1.13722658e+00,\n",
      "         8.76002014e-02, -3.81218910e-01, -3.11869055e-01,\n",
      "         4.37887698e-01, -1.37118995e-02,  4.18663144e-01,\n",
      "         6.16097927e-01,  4.11310904e-02, -4.50686693e-01,\n",
      "        -8.32464635e-01, -1.22572288e-01, -5.28410435e-01,\n",
      "         3.62556218e-03, -4.80408043e-01, -4.09289092e-01,\n",
      "         3.36103827e-01, -1.96403921e-01, -2.38947547e-03,\n",
      "        -2.40042433e-01, -6.04247034e-01,  2.31371403e-01,\n",
      "         1.24280140e-01,  4.01561588e-01,  4.36118573e-01,\n",
      "         4.05807495e-01,  2.10809652e-02, -2.36622110e-01,\n",
      "        -2.21643493e-01, -8.07343006e-01,  7.08524510e-02,\n",
      "        -8.48622680e-01,  1.10559026e-02,  5.13370514e-01,\n",
      "        -1.64441660e-01, -4.07519937e-01, -2.17397586e-01,\n",
      "        -4.60593820e-01,  5.30118287e-01,  2.40217045e-01,\n",
      "         1.33833438e-01,  5.59603751e-01,  3.28083754e-01,\n",
      "         2.46703848e-01,  1.16818404e+00, -6.94000840e-01,\n",
      "         1.13665365e-01, -1.90860659e-01, -1.60431638e-01,\n",
      "         4.46497440e-01, -2.74127632e-01, -7.94055462e-02,\n",
      "        -1.36253551e-01, -9.17736650e-01,  3.03198010e-01,\n",
      "        -4.21359017e-02, -3.71193826e-01,  4.96033043e-01,\n",
      "         4.23734665e-01,  2.65220731e-01,  2.29484320e-01,\n",
      "         1.75113112e-01, -8.52245465e-03, -7.19752014e-02,\n",
      "         5.04485033e-02, -4.93971378e-01,  4.12294298e-01,\n",
      "         4.60886359e-01, -1.00163318e-01,  8.73046592e-05,\n",
      "         1.56556368e-02,  1.84312567e-01,  1.20623939e-01,\n",
      "         2.66871899e-01,  3.72901708e-01,  3.37007493e-02,\n",
      "        -1.25049070e-01, -5.76412797e-01,  3.23601961e-01,\n",
      "        -8.96664932e-02,  3.18294585e-01,  2.13168487e-02,\n",
      "         8.73643234e-02, -5.53453937e-02, -8.35335106e-02,\n",
      "        -2.03166455e-02, -6.88339651e-01,  5.92037797e-01,\n",
      "        -4.25093293e-01,  2.26889610e-01, -1.13530606e-02,\n",
      "        -4.04689342e-01, -1.42740354e-01,  4.02623057e-01,\n",
      "        -3.80865067e-01, -2.98699420e-02,  2.26771668e-01,\n",
      "        -1.94398910e-01,  2.29484320e-01, -2.96340585e-02,\n",
      "        -3.36165100e-01, -5.07534683e-01,  3.75928320e-02,\n",
      "        -7.56038308e-01,  1.19916290e-01,  5.38610101e-01,\n",
      "         6.71412706e-01,  1.94809407e-01,  1.07886210e-01,\n",
      "        -1.06532186e-01,  3.06854218e-01,  6.87806606e-01,\n",
      "        -6.12424910e-02, -3.04202825e-01, -6.67857602e-02,\n",
      "         6.44835904e-02,  7.28496552e-01, -5.51880836e-01,\n",
      "         6.49553537e-02, -1.89799175e-01,  1.04517055e+00,\n",
      "        -2.02065140e-01, -3.13402295e-01, -4.02330518e-01,\n",
      "         6.14170991e-02,  2.97654748e-01, -1.22218460e-01,\n",
      "        -4.99868453e-01,  1.19916290e-01,  4.17719632e-01,\n",
      "        -2.86393613e-01,  2.66046315e-01, -6.67463899e-01,\n",
      "         2.18161896e-01, -2.10203126e-01, -2.92880416e-01,\n",
      "         2.79996870e-03,  9.34972987e-02,  1.13783307e-01,\n",
      "         5.92745423e-01,  5.22687912e-01,  6.46173120e-01,\n",
      "         8.11133981e-02, -9.54456478e-02,  6.85329795e-01,\n",
      "        -1.89013425e-02, -3.63055855e-01, -2.50343233e-02,\n",
      "         2.64395148e-01, -3.67537647e-01, -2.90521562e-01,\n",
      "        -9.63891819e-02, -5.77946007e-01, -4.95622545e-01,\n",
      "         1.59308895e-01,  3.05556864e-01, -5.29943645e-01,\n",
      "        -7.16291904e-01, -2.81008128e-02,  7.75352912e-03,\n",
      "        -2.39924490e-01,  2.78548151e-01,  4.20078456e-01,\n",
      "        -1.51272025e-02, -1.08812936e-02, -4.93027836e-01,\n",
      "        -7.82261267e-02, -3.75361666e-02,  5.14196098e-01,\n",
      "        -2.09849298e-01, -4.14950281e-01, -3.47133696e-01,\n",
      "        -5.13667643e-01,  1.94809407e-01, -1.33540884e-01,\n",
      "        -6.54883981e-02, -3.83223921e-01, -3.14345837e-01,\n",
      "         6.38938770e-02, -9.38494444e-01,  3.25135231e-01,\n",
      "        -6.26577958e-02,  1.90799385e-01,  7.86366165e-02,\n",
      "        -6.04168959e-02, -6.93411171e-01,  1.90327615e-01,\n",
      "         1.69687778e-01, -1.74938500e-01,  6.11734092e-01,\n",
      "        -3.20714712e-01,  6.62527159e-02, -1.56893387e-01,\n",
      "        -4.57881153e-01, -1.83430314e-01,  4.41975817e-02,\n",
      "        -1.14670180e-01, -4.82059240e-01, -4.59178507e-01,\n",
      "        -7.04419613e-02, -1.74702615e-01, -1.38966218e-01,\n",
      "        -2.56908119e-01,  3.22854482e-02,  7.26373613e-01,\n",
      "         4.31361049e-02,  3.86543088e-02,  3.00367415e-01,\n",
      "        -2.69645840e-01, -7.46097788e-03,  4.74095851e-01,\n",
      "         7.14225590e-01, -8.23540911e-02, -4.29103315e-01,\n",
      "         4.17365789e-01,  9.69176143e-02, -2.64496263e-02,\n",
      "         7.64115036e-01,  2.82754228e-02, -4.30164784e-01,\n",
      "         5.93453050e-01, -5.72324656e-02, -5.43860793e-01,\n",
      "         2.00824440e-01, -2.68112600e-01, -8.77872288e-01,\n",
      "        -5.10247350e-01, -3.73002812e-02,  4.61122245e-01,\n",
      "         3.83004844e-02,  5.24810851e-01, -1.15377828e-01,\n",
      "         7.33292326e-02,  3.12987208e-01,  2.51893282e-01,\n",
      "        -2.77076185e-01, -3.64589095e-01,  2.30427861e-01,\n",
      "        -4.70894612e-02,  1.25891473e-02, -5.13431787e-01,\n",
      "         9.36152413e-02,  1.64498329e-01,  3.32447618e-01,\n",
      "        -2.54903108e-01,  1.34187266e-01,  2.09552139e-01,\n",
      "        -6.16748929e-01, -7.96964169e-01,  3.37007493e-02,\n",
      "        -7.10316673e-02, -4.10940260e-01,  2.78036539e-02,\n",
      "         1.45155862e-01, -6.89990819e-01,  1.82071671e-01,\n",
      "        -5.30061603e-01,  6.01001382e-01, -5.21805644e-01,\n",
      "         2.37386435e-01,  7.03846693e-01,  5.30000329e-01,\n",
      "        -1.19387850e-01, -2.65282005e-01,  2.35577449e-02,\n",
      "         4.10131477e-02, -3.19063514e-01,  2.43991181e-01,\n",
      "         7.42885470e-01,  4.18387428e-02,  2.16982484e-01,\n",
      "         2.89516747e-01, -4.30046856e-01, -2.60446370e-01,\n",
      "        -2.61154026e-01,  2.69112796e-01, -6.78472370e-02,\n",
      "        -1.68687567e-01, -4.24149752e-01, -2.66225547e-01,\n",
      "        -4.40543681e-01, -4.74432856e-02, -4.38774556e-01,\n",
      "        -5.80979092e-03, -2.60446370e-01,  2.25002527e-01,\n",
      "        -1.73523188e-01, -8.94306079e-02,  8.02328229e-01,\n",
      "         3.39288235e-01, -3.16350847e-01, -2.06311047e-01,\n",
      "         3.43062401e-01, -6.35147870e-01, -1.69866994e-01,\n",
      "        -6.16748929e-01,  2.15921000e-01,  5.41558623e-01,\n",
      "        -2.48652190e-01, -5.61709888e-02, -4.42666650e-01,\n",
      "         2.76071370e-01, -4.15422052e-01,  4.69142288e-01,\n",
      "         9.90405679e-02, -1.89445347e-01, -1.59723982e-01,\n",
      "         1.08711809e-01,  3.83044690e-01, -1.56303674e-01,\n",
      "        -1.59841925e-01,  4.26643342e-02,  1.84862427e-02,\n",
      "        -1.23869650e-01,  2.87865579e-01,  2.81574801e-02,\n",
      "        -4.56701726e-01, -8.69498432e-01,  2.12146863e-01,\n",
      "         4.28806156e-01, -3.34513903e-01, -1.56539559e-01,\n",
      "         1.89384073e-01, -2.83916831e-01, -3.06955352e-02,\n",
      "        -1.17500782e-01,  1.49401769e-01, -1.94280967e-01,\n",
      "         5.85433006e-01,  4.50153649e-01,  8.33582819e-01,\n",
      "         7.38875449e-01,  1.30609153e-02, -5.18739164e-01,\n",
      "         3.60517800e-01,  5.82366526e-01, -6.70884252e-01,\n",
      "         4.12294298e-01,  2.38212034e-01,  2.68202671e-03,\n",
      "         7.76930824e-02,  2.84563214e-01,  3.04613322e-01,\n",
      "        -3.23073536e-01, -2.27776468e-01,  8.15851688e-02,\n",
      "         1.36428162e-01,  3.65235478e-01, -6.39983475e-01,\n",
      "        -4.96448159e-01,  4.10525173e-01,  2.09552139e-01,\n",
      "        -3.92895162e-01,  2.39155561e-01,  7.65136629e-02,\n",
      "        -3.19299400e-01, -1.87676221e-01, -2.43580684e-01,\n",
      "        -4.53399360e-01,  5.49224854e-01, -4.10114676e-01,\n",
      "         1.58601239e-01, -3.01961929e-01, -6.47413790e-01,\n",
      "        -5.71341276e-01,  5.19857347e-01, -2.30489135e-01,\n",
      "        -1.70692593e-01,  3.29499066e-01,  1.36428162e-01,\n",
      "         5.02126180e-02, -2.43108928e-01,  8.33582819e-01,\n",
      "         4.34899293e-02, -9.53237176e-01,  7.12062791e-02,\n",
      "         1.04701780e-01, -1.28233492e-01,  1.54591218e-01,\n",
      "         6.62095249e-01,  7.25036412e-02, -1.04173347e-01,\n",
      "         3.04495394e-01, -7.82261267e-02,  7.14225590e-01,\n",
      "        -6.31845474e-01,  4.97330427e-01, -5.70279777e-01,\n",
      "        -2.20817894e-01, -6.15097702e-01, -1.62908420e-01,\n",
      "         1.41617596e-01,  2.82794058e-01,  3.68066072e-01,\n",
      "         6.84504211e-01, -3.43517326e-02,  5.85197151e-01,\n",
      "         5.51263290e-03, -3.42651904e-01, -1.17972553e-01,\n",
      "         1.26756921e-01, -3.22955608e-01,  9.97482240e-02,\n",
      "         8.94872770e-02, -7.15466261e-01,  5.12740947e-02,\n",
      "        -5.32420456e-01, -2.09023714e-01, -4.95662391e-02,\n",
      "         1.50699124e-01,  5.14314055e-01, -2.37447709e-01,\n",
      "        -5.16144454e-01, -5.60962379e-01,  2.01885924e-01,\n",
      "        -5.63910902e-01,  4.06593233e-02, -3.25668275e-01,\n",
      "         6.82027459e-01,  1.54197533e-02,  2.41632342e-01,\n",
      "         6.90873086e-01,  4.10131477e-02,  5.15257597e-01,\n",
      "         3.59338373e-01, -1.88147992e-01,  2.41750285e-01,\n",
      "        -2.77783841e-01,  1.46099389e-01, -3.25550318e-01,\n",
      "        -1.06650129e-01, -3.14463764e-01,  4.04628068e-01,\n",
      "        -7.12989509e-01,  6.17867053e-01, -6.27127767e-01,\n",
      "        -8.70717689e-02,  3.87722515e-02,  3.09920698e-01,\n",
      "         2.20245011e-02,  9.12898045e-04,  2.67815441e-01,\n",
      "         1.12917861e-02, -1.00399204e-01,  1.56596228e-01,\n",
      "        -8.80153030e-02, -1.83194429e-01, -4.39364254e-01,\n",
      "         8.93261433e-01,  5.15257597e-01,  1.32182240e-01,\n",
      "        -9.73287284e-01,  3.43298286e-01, -3.11515242e-01,\n",
      "         2.27479309e-01, -1.00753032e-01,  3.77737314e-01,\n",
      "        -1.29884690e-01, -1.04409233e-01,  4.82941508e-01,\n",
      "        -6.05190575e-01,  2.53072709e-01, -6.33654445e-02,\n",
      "         2.61210710e-01,  1.36428162e-01,  3.53087455e-01,\n",
      "        -8.81332457e-02,  2.22171932e-01,  3.90475035e-01,\n",
      "        -3.66829991e-01,  4.25739676e-01, -7.07957819e-02,\n",
      "        -3.30267996e-01,  2.97536820e-01, -5.54239690e-01,\n",
      "         5.05940199e-01, -1.00796223e+00, -2.50893086e-01,\n",
      "        -1.71989948e-01,  4.68316704e-01,  5.51465750e-01,\n",
      "        -3.96079570e-01,  2.24176943e-01,  9.05088987e-03,\n",
      "         7.80469105e-02,  1.41381711e-01,  4.30457354e-01,\n",
      "        -1.86142981e-01, -6.63538463e-03, -2.18694940e-01,\n",
      "         1.99291199e-01,  8.02878067e-02, -4.63424414e-01,\n",
      "         2.88691163e-01, -4.70618874e-01, -1.47733763e-02,\n",
      "        -2.29427665e-01, -1.23751707e-01, -4.29221272e-01,\n",
      "        -2.74599403e-01, -6.73754662e-02,  2.53662407e-01,\n",
      "        -3.04910481e-01,  8.61849040e-02, -1.71518177e-01,\n",
      "        -3.70604128e-01, -1.90506831e-01, -3.02433699e-01,\n",
      "         2.78430223e-01,  3.86818826e-01,  3.55446279e-01,\n",
      "        -1.59016341e-01, -5.22008166e-03, -2.11972252e-01,\n",
      "         1.41499653e-01, -1.12311341e-01, -1.66800499e-01,\n",
      "        -1.04291290e-01, -1.43919766e-01,  5.49224854e-01,\n",
      "        -3.21108364e-02,  1.20388053e-01, -1.81936920e-02,\n",
      "        -1.37786791e-01, -4.14360583e-01, -6.98921038e-03,\n",
      "         2.46192235e-02, -5.18857121e-01,  1.91860855e-01,\n",
      "         1.52350321e-01, -3.03613126e-01,  1.41145840e-01,\n",
      "         3.54384810e-01,  2.42929712e-01,  2.41632342e-01,\n",
      "         2.53780365e-01, -1.05706595e-01, -3.20478827e-01,\n",
      "        -1.40499458e-01,  1.56556368e-02, -7.09137246e-02,\n",
      "         2.35735252e-01,  4.31361049e-02,  2.44345009e-01,\n",
      "         4.72680539e-01,  3.15346032e-01, -3.91715735e-01,\n",
      "        -4.24385637e-01, -2.67404944e-01, -1.45453021e-01,\n",
      "         1.66857168e-01,  1.52586192e-01,  2.84917027e-01,\n",
      "         3.87644440e-01, -9.52097625e-02, -3.62937897e-01,\n",
      "        -1.98762760e-01,  5.93571007e-01,  4.37180042e-01,\n",
      "         1.79712832e-01, -7.99087107e-01,  3.67004603e-01,\n",
      "        -6.27009869e-01, -1.97465405e-01,  4.69024360e-01,\n",
      "         4.63009328e-01, -7.69287646e-02,  3.87172669e-01,\n",
      "        -3.53738427e-01,  3.45263444e-02,  6.21247515e-02,\n",
      "        -1.68097869e-01, -9.75686014e-02,  2.27597252e-01,\n",
      "        -3.59399647e-01,  5.72577357e-01,  4.31872636e-01,\n",
      "        -3.15211266e-02, -5.72874486e-01, -2.50421315e-01,\n",
      "        -5.25461853e-01, -2.87926853e-01,  3.06146562e-01,\n",
      "         5.09202704e-02,  8.80719721e-02, -5.38121499e-02,\n",
      "        -2.15274632e-01,  1.34069324e-01,  2.09080368e-01,\n",
      "        -1.63969904e-01,  1.93865865e-01,  6.40276015e-01,\n",
      "         4.25463952e-02, -6.64987147e-01, -2.10792840e-01,\n",
      "        -1.15613714e-01, -1.48637444e-01, -1.90624774e-01,\n",
      "         1.58011526e-01, -6.70648336e-01,  1.72518387e-01,\n",
      "         5.10539889e-01,  4.10525173e-01,  9.71534997e-02,\n",
      "         4.62025926e-02, -8.27079192e-02, -4.13299114e-01,\n",
      "        -8.45556200e-01, -1.92511842e-01,  2.45524421e-01,\n",
      "         7.79093623e-01,  3.93541515e-01, -3.42298061e-01,\n",
      "        -2.01475427e-01,  6.11616135e-01,  1.05881199e-01,\n",
      "        -3.49020749e-01,  4.83295321e-01, -8.05068761e-03,\n",
      "         2.88337350e-01, -3.96669298e-01,  2.54488021e-01,\n",
      "        -2.03716323e-01,  5.78120649e-01,  1.28408104e-01,\n",
      "        -8.68672848e-01, -2.78963268e-01,  3.68851833e-02,\n",
      "        -3.93013090e-01, -5.47634959e-01,  4.35528845e-01,\n",
      "        -2.41929501e-01, -5.23928642e-01,  1.33243725e-01,\n",
      "        -1.42150640e-01, -4.00443435e-01,  3.07090104e-01,\n",
      "        -1.27761737e-01, -5.23968451e-02, -1.09952502e-01,\n",
      "        -2.85803884e-01, -1.03701577e-01,  6.42988682e-01,\n",
      "        -2.66461432e-01,  4.49917763e-01, -1.11131921e-01,\n",
      "         3.26432586e-01, -1.41796812e-01, -8.05849656e-02,\n",
      "        -3.39821279e-01,  1.22628950e-01,  1.91153198e-01,\n",
      "        -2.72948235e-01, -2.18459055e-01, -1.94752738e-01,\n",
      "         1.46099389e-01,  1.80892259e-01, -2.66521092e-04,\n",
      "         5.73756754e-01,  2.19065584e-02,  1.09537400e-01,\n",
      "         4.62301672e-01, -9.02561992e-02, -3.64589095e-01,\n",
      "         3.31975847e-01,  2.09630225e-02, -1.01106860e-01,\n",
      "         1.62257433e-01, -1.83666199e-01, -7.04419613e-02,\n",
      "         2.73358732e-01, -3.36440839e-02, -1.94045082e-01,\n",
      "         5.47573686e-01,  2.33140528e-01, -4.27654618e-03,\n",
      "         1.11306526e-01,  1.41145840e-01, -4.25565064e-01,\n",
      "         3.86582941e-01,  4.33052063e-01, -3.66712034e-01,\n",
      "         2.68202671e-03,  9.39690694e-02, -4.02802259e-01,\n",
      "         5.92745423e-01,  1.11778297e-01,  2.07665071e-01,\n",
      "         2.24412829e-01, -5.79833090e-01,  1.81364030e-01,\n",
      "         9.14922878e-02, -3.04910481e-01, -3.55861396e-01,\n",
      "        -1.11013979e-01,  3.11100125e-01,  1.91624969e-01,\n",
      "         1.17911279e-01,  8.35901797e-02, -2.27658525e-01,\n",
      "         3.33744973e-01, -4.29614931e-02, -9.04920846e-02,\n",
      "         4.74095851e-01, -2.05957219e-01,  3.67122531e-01,\n",
      "        -1.05588652e-01, -3.99381965e-01,  4.00618047e-01,\n",
      "        -3.54210198e-01,  1.41853482e-01,  1.62021548e-01,\n",
      "        -7.69686187e-03, -6.46234393e-01,  3.44949454e-01,\n",
      "        -2.27658525e-01, -5.83135486e-01,  2.06603602e-01,\n",
      "        -3.65886450e-01,  4.12766069e-01,  2.53308594e-01,\n",
      "        -6.07077658e-01, -3.09038460e-01, -5.06119370e-01,\n",
      "        -3.73552680e-01, -4.68535759e-02, -2.45625544e-02,\n",
      "        -2.21289665e-01,  7.63957202e-02, -3.91715735e-01,\n",
      "        -3.48666936e-01, -1.86850622e-01, -3.42769831e-01,\n",
      "        -1.82486773e-01,  4.01679516e-01,  8.30004662e-02,\n",
      "         3.23366076e-01,  8.05236921e-02, -5.70279777e-01,\n",
      "        -3.87155861e-02, -1.79774120e-01, -2.71061152e-01,\n",
      "        -1.72343776e-01, -2.06704717e-02,  5.43405861e-02,\n",
      "        -1.30474389e-01,  4.43548888e-01,  7.96980932e-02,\n",
      "         3.55800122e-01,  4.69102450e-02,  2.76307255e-01,\n",
      "         1.31474599e-01, -5.85730195e-01,  2.45996192e-01,\n",
      "        -3.40764821e-01, -9.92197841e-02, -7.05599040e-02,\n",
      "        -3.07269335e-01,  8.65387246e-02,  3.22422564e-01,\n",
      "        -1.90742716e-01,  1.93158224e-01,  5.32595038e-01,\n",
      "        -6.26577958e-02,  3.67830187e-01, -4.36297774e-01,\n",
      "         2.34673768e-01,  9.75073278e-02,  1.67328939e-01,\n",
      "        -1.55124247e-01,  1.05472386e+00, -1.48283616e-01,\n",
      "         6.69205189e-03,  4.26801145e-01,  1.86199650e-01,\n",
      "        -2.30960906e-01,  1.89973786e-01, -1.05116881e-01,\n",
      "        -7.53089726e-01, -2.74953246e-01, -3.39979082e-02,\n",
      "        -9.89839062e-02, -1.46632433e-01,  8.80719721e-02,\n",
      "         1.38433173e-01, -3.81218910e-01, -7.79036999e-01,\n",
      "        -1.54888377e-01, -3.07623148e-01,  1.91271141e-01,\n",
      "        -2.50539273e-01,  1.69805720e-01,  5.65972626e-01,\n",
      "         4.83255461e-02, -3.48431051e-01,  1.97168246e-01,\n",
      "        -1.68333754e-01,  2.32786700e-01, -3.55389625e-01,\n",
      "         3.31622034e-01,  3.44084017e-02,  4.04628068e-01,\n",
      "        -5.67331254e-01, -7.78722987e-02,  2.40806744e-01,\n",
      "         3.33980858e-01, -8.76614824e-02, -4.17898834e-01,\n",
      "        -5.18071391e-02,  4.80818540e-01,  4.07812506e-01,\n",
      "         4.99689251e-01, -9.55635905e-02,  5.15493453e-01,\n",
      "         2.69584566e-01, -3.94428402e-01,  6.10632747e-02,\n",
      "         1.64026558e-01,  6.49553537e-02,  1.04465902e-01,\n",
      "         3.15379445e-03, -4.86423075e-01, -1.32361472e-01,\n",
      "         7.76616871e-01,  4.66665506e-01, -1.33304998e-01,\n",
      "        -2.25063816e-01, -2.18694940e-01,  2.62625992e-01,\n",
      "        -9.85317409e-01, -9.72147733e-02,  1.91624969e-01,\n",
      "        -3.18237931e-01, -6.12974763e-01, -2.21879378e-01,\n",
      "        -4.09407020e-01,  7.18471527e-01, -2.86983311e-01,\n",
      "        -2.30960906e-01],\n",
      "       [-7.07041249e-02, -1.54887974e+00, -1.49496486e-02,\n",
      "         1.39596260e+00,  7.90591717e-01, -2.15205401e-01,\n",
      "         1.86584875e-01, -8.36347759e-01,  8.59881192e-02,\n",
      "        -1.13302302e+00, -1.39133501e+00, -5.88265955e-01,\n",
      "        -8.29612911e-01,  6.37139022e-01, -1.64736524e-01,\n",
      "        -2.07362264e-01,  4.63225961e-01,  3.98946345e-01,\n",
      "         6.52143300e-01, -9.20320511e-01, -1.24924071e-01,\n",
      "         1.39014542e-01, -1.70540154e+00, -2.04463720e-01,\n",
      "         1.22690880e+00, -4.21448760e-02, -1.95532292e-02,\n",
      "        -2.07277015e-01, -9.08300042e-01,  2.98605353e-01,\n",
      "        -4.17080939e-01, -4.75307703e-01, -6.28675163e-01,\n",
      "         8.46431434e-01,  3.35584506e-02,  1.21282235e-01,\n",
      "         3.99628371e-01,  2.04487696e-01, -5.28930902e-01,\n",
      "        -1.72835410e-01, -1.99433878e-01, -1.34205961e+00,\n",
      "        -7.44446635e-01,  2.97156066e-01,  2.43362367e-01,\n",
      "         1.10065138e+00,  2.11969838e-02,  1.38692594e+00,\n",
      "         1.47539690e-01, -9.32255685e-01,  1.61181927e+00,\n",
      "         4.56832111e-01,  9.83515799e-01,  2.83601075e-01,\n",
      "        -1.95512310e-01,  5.45493662e-01,  6.16678655e-01,\n",
      "        -3.93315740e-02, -5.07959008e-01,  5.14291584e-01,\n",
      "         8.21878970e-01,  8.04913938e-01, -6.85878873e-01,\n",
      "         3.53336811e-01, -7.91440234e-02,  8.47945958e-02,\n",
      "         1.18274856e+00, -2.38649562e-01,  4.17360663e-01,\n",
      "         5.50097227e-01, -9.43423629e-01, -5.78717768e-01,\n",
      "         7.99884140e-01,  1.49280822e+00, -7.50584781e-01,\n",
      "         1.18931293e+00, -1.59450933e-01, -2.36688778e-01,\n",
      "         1.36096012e-02,  1.38428307e+00,  1.69960842e-01,\n",
      "         4.50097233e-01,  1.26569831e+00, -3.12051088e-01,\n",
      "        -1.12526512e+00,  2.59048641e-01, -1.46492705e-01,\n",
      "         1.23577499e+00, -3.50073248e-01, -1.08562315e+00,\n",
      "         2.69619823e-01, -1.30991983e+00,  2.80105770e-01,\n",
      "         7.07727253e-01,  1.39127374e+00,  4.86329138e-01,\n",
      "        -2.49135494e-01,  1.45504189e+00,  2.06618980e-01,\n",
      "        -6.34557486e-01,  7.85817623e-01,  7.19216242e-02,\n",
      "         3.91273707e-01, -5.14693916e-01, -4.78567258e-02,\n",
      "         1.17959428e+00,  4.94087011e-01, -1.17166184e-01,\n",
      "        -3.13841373e-01,  4.23498780e-01, -1.26993692e+00,\n",
      "        -3.57916415e-01,  1.38503030e-01,  3.15826148e-01,\n",
      "        -1.14779145e-01, -1.64794195e+00,  5.32876432e-01,\n",
      "         7.06618965e-01,  5.60412645e-01, -5.03696442e-01,\n",
      "        -1.02313375e+00,  1.64419487e-01, -5.00968397e-01,\n",
      "         3.22219998e-01,  1.03918505e+00, -2.50243753e-01,\n",
      "         4.89994943e-01,  7.99457848e-01, -1.33933163e+00,\n",
      "         4.92893487e-01,  5.10114312e-01,  4.26823586e-01,\n",
      "        -4.99519140e-01,  1.04658194e-01,  6.21176995e-02,\n",
      "        -5.26543856e-01,  5.76646440e-03,  1.24762499e+00,\n",
      "        -5.16077913e-02, -7.53057063e-01,  5.44896901e-01,\n",
      "         2.95621544e-01,  1.97477080e-02, -1.66916955e+00,\n",
      "        -3.26288104e-01, -2.22812761e-02,  6.24010265e-01,\n",
      "         4.07386243e-01,  4.82663304e-01,  1.52058020e-01,\n",
      "        -6.31914675e-01, -1.09150553e+00, -1.01224162e-01,\n",
      "         4.62799698e-01,  4.35945481e-01,  3.08238745e-01,\n",
      "        -8.60814929e-01, -3.92463244e-02,  1.38973916e+00,\n",
      "         4.17957425e-01, -1.78376764e-01, -6.93381011e-01,\n",
      "         5.92808247e-01,  8.09347034e-01, -1.79740787e-01,\n",
      "        -6.05571985e-01, -5.24668336e-01, -9.17612389e-02,\n",
      "        -1.15501785e+00, -3.77779990e-01,  1.55979589e-01,\n",
      "         4.51034993e-01, -5.39161086e-01,  5.87948918e-01,\n",
      "        -1.21940270e-01,  1.39408696e+00,  1.79574266e-02,\n",
      "        -1.29261374e+00,  1.05766468e-01,  1.19630361e+00,\n",
      "        -7.93977797e-01,  7.91358948e-01,  2.18789969e-02,\n",
      "        -3.57319653e-01,  2.80361533e-01, -2.69084334e-01,\n",
      "        -1.41462862e-01,  2.18895197e-01, -4.45554942e-01,\n",
      "        -7.01073632e-02,  1.48138452e+00,  1.78315490e-01,\n",
      "        -3.62434715e-01,  2.95962542e-01, -4.58257407e-01,\n",
      "         9.41231072e-01, -7.53276842e-03, -6.87498689e-01,\n",
      "        -6.10707067e-02,  1.93214510e-02, -6.28589869e-01,\n",
      "        -1.86047399e+00,  4.99628365e-01, -4.18018699e-01,\n",
      "        -3.10772330e-01, -1.02843933e-01,  9.07215714e-01,\n",
      "        -3.85196865e-01, -5.42315364e-01,  6.10946827e-02,\n",
      "         1.79954314e+00,  6.15314603e-01, -4.35239494e-01,\n",
      "        -4.87754434e-01, -4.35088985e-02, -5.16930409e-02,\n",
      "        -3.36944520e-01, -1.12168455e+00, -1.85793638e-01,\n",
      "         2.17104912e-01,  2.24266037e-01, -9.07618046e-01,\n",
      "         1.29084742e+00,  5.00395596e-01,  3.82663310e-01,\n",
      "        -4.80272286e-02, -5.38564324e-01, -1.46021819e+00,\n",
      "        -2.20405743e-01,  8.89653921e-01,  2.09688038e-01,\n",
      "         1.36096012e-02,  1.10114291e-01, -1.27726853e+00,\n",
      "         1.04097533e+00,  8.38247299e-01, -3.75989705e-01,\n",
      "         5.02271175e-01, -4.93977785e-01,  2.50523508e-01,\n",
      "        -4.62093711e-01,  2.72688895e-01,  7.07045257e-01,\n",
      "        -1.02758683e-01, -2.08641037e-01,  6.77292466e-01,\n",
      "        -1.35433578e+00, -7.65864775e-02,  4.27590847e-01,\n",
      "        -3.35751027e-01,  1.13439098e-01,  6.19321465e-01,\n",
      "        -8.57936367e-02,  7.75672674e-01, -7.85793662e-01,\n",
      "        -4.81360555e-01, -2.72153407e-01, -1.08144581e+00,\n",
      "         4.11478311e-01,  2.71154344e-01,  2.34496221e-01,\n",
      "         6.77462995e-01,  2.73285657e-01, -4.52716053e-01,\n",
      "         6.69619858e-01,  5.71751118e-01,  6.04979210e-02,\n",
      "        -8.40610325e-01,  9.54700828e-01,  9.48392212e-01,\n",
      "        -5.02247155e-01, -2.54847348e-01,  3.96729797e-01,\n",
      "         7.49159455e-01,  6.73967659e-01,  7.22987294e-01,\n",
      "         8.79338503e-01,  4.27676111e-01,  3.13780099e-01,\n",
      "        -2.41718620e-01, -8.09067309e-01,  1.72092125e-01,\n",
      "         2.79082745e-01, -1.77215338e+00, -9.85026360e-01,\n",
      "        -5.78311495e-02,  7.09006011e-01,  9.61520910e-01,\n",
      "         4.60668415e-01, -1.16143167e-01, -2.88606942e-01,\n",
      "         5.71921647e-01, -4.91505474e-01,  7.03018457e-02,\n",
      "        -7.17762947e-01, -3.07959020e-01, -2.81701565e-01,\n",
      "        -1.03558052e+00, -9.39672589e-01,  6.88801408e-01,\n",
      "         5.29957898e-02, -2.47856721e-01, -1.31232679e-01,\n",
      "         7.95195282e-01, -1.44743049e+00,  5.99864125e-02,\n",
      "         4.99116838e-01,  4.73691933e-02, -9.22878027e-01,\n",
      "         1.69960842e-01, -7.41377592e-01, -2.81701565e-01,\n",
      "         1.00934708e+00, -3.99007618e-01,  7.36542225e-01,\n",
      "         2.67147541e-01, -1.10991979e+00,  3.65783513e-01,\n",
      "        -9.84088600e-01, -9.12562609e-01, -2.57490128e-01,\n",
      "        -5.94233513e-01, -2.56893396e-01, -3.46066445e-01,\n",
      "        -9.72153425e-01,  3.69790345e-01,  5.33387959e-01,\n",
      "        -1.27396360e-01, -6.37456059e-01, -5.63969254e-01,\n",
      "         3.80105764e-01,  3.10966820e-01,  9.91785228e-01,\n",
      "        -5.06680250e-01,  5.01759648e-01, -5.44020414e-01,\n",
      "        -1.34983748e-01, -3.08641046e-01,  9.73265693e-02,\n",
      "        -9.33619738e-01, -1.10156512e+00,  1.30980927e-02,\n",
      "        -6.94148302e-01, -4.29186642e-01, -1.29679108e+00,\n",
      "        -7.70533621e-01, -4.18530226e-01,  1.48385680e+00,\n",
      "         4.94087011e-01, -1.23389550e-01,  3.13012838e-01,\n",
      "        -1.48112476e-01, -1.51607797e-01,  3.20173979e-01,\n",
      "        -1.24342370e+00, -3.62860978e-01, -2.18615457e-01,\n",
      "        -1.69340104e-01, -4.36794013e-02, -6.85964167e-01,\n",
      "         6.71475381e-02,  1.26567826e-01, -4.15716916e-01,\n",
      "        -4.46151704e-01,  2.07727253e-01, -4.25606072e-01,\n",
      "         8.17531168e-01,  1.25885814e-01, -2.59109914e-01,\n",
      "         1.12972212e+00,  6.85115606e-02, -5.79058766e-01,\n",
      "        -1.90417208e-02,  3.76525193e-01, -9.25606072e-01,\n",
      "         2.73370892e-01,  8.63311231e-01, -2.04207957e-01,\n",
      "         6.33387923e-01,  3.13950598e-01, -3.73261660e-01,\n",
      "        -2.18530208e-01,  1.33739471e+00, -1.53344917e+00,\n",
      "        -4.54335839e-01, -3.46492708e-01, -5.92954755e-01,\n",
      "         1.39178526e+00,  1.58914109e-03, -5.77780008e-01,\n",
      "        -1.98837116e-01, -1.91249728e-01,  9.10114288e-01,\n",
      "        -1.81360558e-01,  2.57002622e-01, -1.40780851e-01,\n",
      "        -2.81275302e-01, -3.45810682e-01,  1.01930149e-01,\n",
      "        -1.19525659e+00, -3.04548979e-01, -7.27907896e-01,\n",
      "         4.00907129e-01, -1.25435576e-01,  1.25459552e-01,\n",
      "         7.58451879e-01, -2.95341820e-01, -6.37115061e-01,\n",
      "        -2.62519985e-01,  6.52654767e-01, -6.04548991e-01,\n",
      "         8.80787790e-01,  2.08494514e-01,  7.32620656e-01,\n",
      "        -2.08555788e-01,  9.56917346e-01, -8.72068167e-01,\n",
      "        -1.44702420e-01, -2.56722867e-01,  2.93660760e-01,\n",
      "         1.09176524e-01,  6.69875562e-01,  1.87863648e-01,\n",
      "         8.17616403e-01,  3.28954875e-01,  1.29125372e-01,\n",
      "        -1.05510306e+00, -8.01650405e-01,  1.20414674e+00,\n",
      "        -1.43464279e+00,  4.83922102e-02, -1.22603238e+00,\n",
      "        -2.02161923e-01, -5.33022940e-01, -1.44086611e+00,\n",
      "         1.22418082e+00,  5.25495503e-03, -2.67143548e-02,\n",
      "         1.04387391e+00, -2.15546414e-01,  1.74223408e-01,\n",
      "         1.45237908e-01, -3.68572831e-01,  1.57855123e-01,\n",
      "        -6.54676855e-01, -7.58939445e-01, -2.21960247e-02,\n",
      "        -1.66100547e-01, -4.53312814e-01, -7.48453498e-01,\n",
      "         6.27931833e-01,  1.04984152e+00, -2.35069007e-01,\n",
      "        -6.81616306e-01, -5.48282981e-01, -1.63031489e-01,\n",
      "         5.56235373e-01,  8.09347034e-01, -2.90226728e-01,\n",
      "         1.00395620e-01, -4.35324758e-01,  2.13865355e-01,\n",
      "        -1.31409717e+00,  1.26655078e+00, -6.00115895e-01,\n",
      "        -8.21002483e-01, -3.26032341e-01,  1.47439396e+00,\n",
      "         4.37991530e-01,  2.39696562e-01, -7.72409141e-01,\n",
      "         5.85561872e-01,  9.43532884e-01, -8.51948798e-01,\n",
      "         9.73882377e-01,  7.11393058e-01,  1.02801704e+00,\n",
      "         4.94428009e-01,  9.18704718e-02,  3.17957431e-01,\n",
      "        -2.79931258e-02,  3.32961679e-01, -1.91249728e-01,\n",
      "        -7.11113334e-01,  9.06533718e-01,  3.13012838e-01,\n",
      "         8.47454429e-01,  4.18980449e-01,  2.51035005e-01,\n",
      "         7.53316805e-02, -8.09343010e-02,  1.00225121e-01,\n",
      "        -2.09172536e-02,  3.37289535e-02, -4.11624849e-01,\n",
      "         4.89037186e-02, -2.51778305e-01,  8.31748173e-02,\n",
      "         4.86499637e-01, -5.52716076e-01, -2.44787663e-01,\n",
      "         1.74734920e-01,  1.44982144e-01,  1.31616712e+00,\n",
      "         2.90165454e-01, -7.95086026e-01, -5.84259093e-01,\n",
      "        -1.08042276e+00,  3.27505589e-01, -5.87328136e-01,\n",
      "        -1.54762089e-01, -1.50420797e+00, -1.24887979e+00,\n",
      "         2.69705087e-01, -1.93722025e-01,  5.18809915e-01,\n",
      "         4.68852580e-01, -8.67549837e-01, -5.75563431e-01,\n",
      "        -6.37029767e-01,  4.72006887e-01,  6.85968101e-02,\n",
      "         5.66295028e-01,  8.28784347e-01, -4.11880583e-01,\n",
      "        -8.43167901e-01,  1.57258362e-01,  3.98605347e-01,\n",
      "         2.60156929e-01, -1.52952766e+00, -3.99283357e-02,\n",
      "         6.67403281e-01, -8.53994846e-01,  8.66501499e-03,\n",
      "        -1.22364533e+00,  6.25459552e-01, -6.21173024e-01,\n",
      "         1.68000057e-01,  1.81469783e-01, -1.46322191e-01,\n",
      "        -2.43423641e-01, -9.19297457e-01,  5.70387065e-01,\n",
      "        -9.05742466e-01, -1.02502927e-01,  1.48573232e+00,\n",
      "        -5.02076685e-01,  7.66957030e-02, -2.34898493e-01,\n",
      "        -6.61857948e-02,  5.41913092e-01,  7.13780105e-01,\n",
      "        -8.17868188e-02,  5.68426311e-01, -5.50670028e-01,\n",
      "        -2.63201982e-01, -3.88200656e-02, -4.36433017e-01,\n",
      "        -4.54165339e-01,  8.53251517e-01, -9.07382220e-02,\n",
      "        -9.05230999e-01, -6.26904815e-02,  1.05405478e-02,\n",
      "        -8.47941995e-01,  3.22134763e-01, -8.05998266e-01,\n",
      "        -3.77438992e-01, -1.81275308e-01, -2.49732256e-01,\n",
      "        -7.49391258e-01,  7.85902858e-01, -8.43935132e-01,\n",
      "        -2.91420251e-01,  4.89227682e-01, -1.83662355e-01,\n",
      "         8.12330842e-01,  9.68767345e-01, -1.83597077e-02,\n",
      "        -2.26032346e-01, -2.99539100e-02,  6.67147517e-01,\n",
      "         7.55674532e-03, -5.24497807e-01, -1.56234944e+00,\n",
      "        -5.31488419e-01, -1.43849909e-01,  3.00054610e-01,\n",
      "        -3.04654203e-02,  9.71836388e-01,  4.10966814e-01,\n",
      "        -7.19979465e-01,  6.64760470e-01,  6.58622384e-01,\n",
      "        -3.00286382e-01,  5.90165436e-01,  5.62353469e-02,\n",
      "        -5.46492696e-01, -9.50755298e-01,  7.23328292e-01,\n",
      "        -5.97558320e-01,  1.15911394e-01, -8.75839218e-02,\n",
      "         3.50949764e-01,  5.18724680e-01,  2.61435688e-01,\n",
      "        -6.03184938e-01, -3.99433881e-01,  4.03805673e-01,\n",
      "         2.40037560e-01, -1.78888261e-01,  8.64334226e-01,\n",
      "        -3.64480764e-01,  1.64140153e+00,  6.09688044e-01,\n",
      "        -3.13585639e-01, -8.09664071e-01, -1.08280981e+00,\n",
      "        -8.40886086e-02, -6.55870378e-01,  1.06620979e+00,\n",
      "        -5.23048520e-01,  5.53336799e-01, -3.83938104e-02,\n",
      "         8.06825422e-03,  1.23072520e-01,  2.96133041e-01,\n",
      "         3.04572940e-01, -4.10346061e-01, -6.19808972e-01,\n",
      "        -2.82298326e-01,  1.40378565e-01, -9.54932570e-01,\n",
      "        -1.84003353e-01, -8.47600996e-01, -7.72579670e-01,\n",
      "         8.74734938e-01, -5.16739905e-01,  2.64163733e-01,\n",
      "         4.60051671e-02,  4.83942091e-01, -1.03506899e+00,\n",
      "        -5.34216464e-01,  1.14634621e+00, -8.93040001e-01,\n",
      "         9.49670970e-01,  4.28187609e-01, -2.32596710e-01,\n",
      "         2.26823583e-01,  1.38162032e-01,  4.22390491e-01,\n",
      "         6.25971079e-01, -2.29698151e-01, -8.51948798e-01,\n",
      "        -2.70789385e-01,  1.76525205e-01, -1.29271895e-01,\n",
      "        -4.85793650e-01,  2.29892641e-01, -1.10173571e+00,\n",
      "        -9.66100514e-01,  3.79679501e-01,  4.10370052e-01,\n",
      "        -7.43167877e-01,  4.86073375e-01,  5.52995801e-01,\n",
      "        -6.34472251e-01, -2.25009322e-01, -2.19979480e-01,\n",
      "        -4.74304669e-02, -8.51352036e-01, -1.14546967e+00,\n",
      "        -6.22707546e-01,  1.84709340e-01, -8.38528387e-03,\n",
      "         5.51120281e-01,  6.28613889e-01, -5.92016995e-01,\n",
      "         6.74820185e-01, -4.46918964e-01, -6.58447891e-02,\n",
      "         4.10625786e-01,  1.18283379e+00,  2.53336787e-01,\n",
      "         6.43342361e-02,  1.09178519e+00, -4.15631652e-01,\n",
      "         8.41913104e-01,  1.30457294e+00,  1.16252400e-01,\n",
      "         1.17089856e+00, -8.41548085e-01,  9.84283090e-01,\n",
      "        -9.75583419e-02,  6.27249837e-01, -8.56978655e-01,\n",
      "        -4.52375054e-01,  1.12332833e+00,  1.24089003e+00,\n",
      "         2.34240457e-01, -1.07888830e+00, -2.44872928e-01,\n",
      "         1.16723275e+00,  1.98690593e-01,  2.35007733e-01,\n",
      "        -9.44020391e-01,  1.70196611e-02, -3.48879755e-01,\n",
      "         1.99372604e-01,  8.12330842e-01, -1.46396923e+00,\n",
      "        -7.31573701e-01,  1.25289053e-01,  1.03202391e+00,\n",
      "         8.07386220e-01,  1.31000906e-01, -3.81445825e-01,\n",
      "         4.18980449e-01, -9.90482450e-01, -8.42315376e-01,\n",
      "         7.22305238e-01, -9.01906192e-01,  1.44129634e-01,\n",
      "         1.66209772e-01, -1.33449227e-01, -6.10431314e-01,\n",
      "         2.62373447e-01, -1.04743052e+00,  2.16934413e-01,\n",
      "        -4.63221967e-02, -4.11283821e-01,  5.06022215e-01,\n",
      "        -6.39672577e-01,  6.29722118e-01, -5.20150006e-01,\n",
      "        -6.02502942e-01, -5.37390783e-02, -5.38564324e-01,\n",
      "         7.28017092e-01, -7.91079223e-01, -5.95512331e-01,\n",
      "        -1.27652124e-01, -5.51031008e-02, -1.24240065e+00,\n",
      "        -2.39075825e-01,  7.92552471e-01, -4.33363974e-01,\n",
      "        -7.97046840e-01, -1.14751577e+00,  9.96218324e-01,\n",
      "        -3.64651263e-01, -3.00456882e-01,  1.31096685e+00,\n",
      "         9.63566959e-01,  6.70423079e-03, -1.36262521e-01,\n",
      "         4.56917346e-01, -3.11474316e-02, -6.64907038e-01,\n",
      "         4.99267355e-02,  1.50588769e-02,  1.39945781e+00,\n",
      "        -1.33193463e-01, -2.97132075e-01,  1.30980927e-02,\n",
      "        -2.08385289e-01,  1.45152658e-01,  9.66445580e-02,\n",
      "        -8.00201118e-01,  8.28017116e-01, -6.18018687e-01,\n",
      "         8.41978341e-02, -1.02424204e+00,  2.47198686e-01,\n",
      "         2.55212337e-01, -4.54165339e-01, -2.50670016e-01,\n",
      "         3.99713606e-01, -4.20491010e-01,  7.56491125e-01,\n",
      "        -5.36177278e-01,  3.56491089e-01,  4.52058017e-01,\n",
      "        -3.70533615e-01, -1.30156517e+00, -2.89033204e-01,\n",
      "         1.78144976e-01,  6.36712730e-01, -1.99604377e-01,\n",
      "         3.17360669e-01, -5.25179803e-01,  2.32961684e-01,\n",
      "         1.57258362e-01, -7.35174268e-02, -7.73687899e-01,\n",
      "        -1.35194874e+00,  4.36542243e-01, -4.19382721e-01,\n",
      "         2.20770732e-01,  2.94342756e-01, -3.61752719e-01,\n",
      "         1.53336793e-01, -5.45128703e-01, -3.19894224e-01,\n",
      "         2.64589995e-01, -1.07189763e+00,  8.84604082e-02,\n",
      "         6.93916500e-01,  2.30725165e-02, -7.63713479e-01,\n",
      "         3.48051190e-01, -1.12136349e-01,  2.45152652e-01,\n",
      "         3.54339816e-02,  1.18468933e-01,  7.78039768e-02,\n",
      "         7.59815931e-01, -7.68422335e-02, -2.17421949e-01,\n",
      "         4.14973617e-01, -1.07394373e+00, -6.91590726e-01,\n",
      "         6.37139022e-01,  9.60924208e-01, -3.97814095e-01,\n",
      "        -6.15972638e-01,  5.52569509e-01, -5.83065569e-01,\n",
      "        -3.87839675e-01, -5.32275699e-02, -8.07638019e-02,\n",
      "        -1.49476498e-01,  2.98179090e-01, -2.73261666e-01,\n",
      "        -4.28675145e-01, -3.65077525e-01,  2.47795448e-01,\n",
      "         1.86329126e-01, -8.40780854e-01,  9.65272009e-01,\n",
      "         8.65848809e-02, -2.54847348e-01, -3.98496121e-01,\n",
      "        -3.34813237e-01, -5.11539578e-01, -1.07905877e+00,\n",
      "        -1.15442109e+00,  1.38076782e-01,  1.04702818e+00,\n",
      "         8.27676117e-01,  3.58366638e-01,  4.11989838e-01,\n",
      "        -1.40318489e+00,  3.48372236e-02, -6.21855021e-01,\n",
      "         5.50608754e-01,  9.41827834e-01,  2.93660760e-01,\n",
      "         1.26718348e-02,  5.92723012e-01, -5.58257401e-01,\n",
      "         9.62458730e-01,  7.57258356e-01,  2.15570390e-01,\n",
      "        -4.15716916e-01,  5.50608754e-01,  6.91444218e-01,\n",
      "         8.68000031e-01,  2.43512895e-02, -5.31914711e-01,\n",
      "        -1.41718611e-01, -8.01670402e-02, -2.25861832e-01,\n",
      "        -3.28504622e-01,  9.92296755e-01,  7.24521816e-01,\n",
      "        -9.22727510e-02, -1.08129531e-01,  1.08494513e-01,\n",
      "         5.86755395e-01, -2.86391733e-04, -2.13415116e-01,\n",
      "         3.01844895e-01,  5.77377737e-01, -9.08555806e-01,\n",
      "        -2.22537026e-01, -2.15461165e-01, -5.55529356e-01,\n",
      "        -5.70874631e-01,  4.00375649e-02,  3.79764766e-01,\n",
      "         4.36371744e-01,  2.77462959e-01, -8.35770965e-02,\n",
      "        -6.25776589e-01,  1.19971359e+00, -2.20255218e-02,\n",
      "         5.76951444e-01,  6.29636884e-01, -3.02949175e-02,\n",
      "         1.18895195e-01,  6.71751142e-01,  3.52399021e-01,\n",
      "         8.71495366e-01,  4.47028190e-01,  8.81810784e-01,\n",
      "         1.17786922e-01,  7.09432304e-01,  1.32972217e+00,\n",
      "        -3.12051088e-01, -7.44020402e-01, -3.33619714e-01,\n",
      "         3.94342750e-01,  5.57684600e-01,  8.43683407e-02,\n",
      "         1.97752818e-01,  3.58963400e-01, -7.35174268e-02,\n",
      "         5.49565740e-02,  4.78400737e-01,  5.66616058e-02,\n",
      "        -2.49476507e-01,  7.81214058e-01,  2.17786923e-01,\n",
      "        -3.28589886e-01, -7.35174268e-02,  8.75928462e-01,\n",
      "        -5.60303450e-01,  2.52399027e-01,  5.20429730e-01,\n",
      "         3.32364917e-01, -1.55464085e-02,  2.33899459e-01,\n",
      "         4.22390491e-01, -6.18615448e-01, -1.22040570e+00,\n",
      "        -6.31573677e-01, -4.71045136e-01, -6.93381011e-01,\n",
      "         8.63822758e-01, -5.70618868e-01, -2.02588186e-01,\n",
      "         3.52634788e-02, -5.86390376e-01, -3.16143155e-01,\n",
      "        -4.14182395e-01,  1.04225409e+00,  3.71069103e-01,\n",
      "        -1.73687920e-01, -4.41121846e-01, -7.21599281e-01,\n",
      "        -3.07788521e-01, -6.87157691e-01,  1.06363222e-01,\n",
      "        -1.07394373e+00,  1.84489554e-03,  1.11563563e-01,\n",
      "        -9.96279597e-01, -7.54506350e-01,  4.12501335e-01,\n",
      "         1.15453029e+00,  9.57920402e-02, -5.68146586e-01,\n",
      "        -4.42485869e-01,  1.28358111e-01, -3.54762107e-01,\n",
      "         7.56746829e-01,  3.34240466e-01, -7.37731755e-02,\n",
      "         5.23990318e-02,  2.95451045e-01,  3.37650508e-01,\n",
      "        -4.26563844e-02, -9.88095403e-01, -7.95000792e-01,\n",
      "         1.10934699e+00, -1.28163636e-01, -4.62946236e-01,\n",
      "        -6.24156833e-01, -1.00201137e-01, -3.80167037e-01,\n",
      "         6.13524377e-01, -7.56040871e-01,  1.07541692e+00,\n",
      "        -3.24327320e-01, -3.88180673e-01,  6.21878982e-01,\n",
      "        -5.92357993e-01, -5.54441065e-02,  1.70301840e-01,\n",
      "        -8.85623157e-01,  7.78741717e-01, -4.37711805e-01,\n",
      "         1.02953166e-01, -8.00817907e-02, -1.02049100e+00,\n",
      "        -6.08555794e-01, -1.30096841e+00, -2.75137216e-01,\n",
      "        -2.90908724e-01,  2.14291617e-01, -6.60900176e-01,\n",
      "         2.91273713e-01,  3.24266046e-01, -3.27225864e-01,\n",
      "        -5.14267623e-01, -6.26288116e-01,  4.05254960e-01,\n",
      "         1.86584875e-01,  2.58622378e-01, -1.17953429e-02,\n",
      "        -7.63116717e-01,  1.73029885e-01, -7.99519122e-01,\n",
      "         5.20600200e-01, -1.55186355e+00,  5.32364905e-01,\n",
      "         9.63822722e-01,  4.40208077e-01, -2.41803870e-01,\n",
      "        -4.64992285e-01, -8.21855009e-01, -6.63457751e-01,\n",
      "         1.25289053e-01],\n",
      "       [ 1.91049743e-02,  7.10615098e-01, -4.07134622e-01,\n",
      "        -1.11203146e+00,  2.17934668e-01, -4.52879429e-01,\n",
      "        -2.27851182e-01,  6.39657259e-01,  1.35203330e-02,\n",
      "        -2.94292003e-01, -7.25048602e-01,  8.78482878e-01,\n",
      "        -3.06118309e-01, -6.40129209e-01, -1.50651723e-01,\n",
      "        -3.51945221e-01,  7.65939429e-02,  2.85495911e-02,\n",
      "         2.31239259e-01, -1.03592902e-01,  5.99579275e-01,\n",
      "         2.79694229e-01, -4.16415006e-01,  2.56780773e-01,\n",
      "        -4.70073335e-02,  3.28067094e-01, -3.12934846e-01,\n",
      "         6.23859540e-02, -3.93173039e-01,  4.68504429e-01,\n",
      "         2.80351251e-01,  5.14659822e-01, -4.16907758e-01,\n",
      "        -2.63494343e-01,  3.48763108e-01, -4.12390769e-01,\n",
      "         4.07155484e-01, -1.84405953e-01,  1.37450114e-01,\n",
      "        -1.61738887e-01, -1.53854683e-01, -1.37458611e-02,\n",
      "         2.76168389e-03,  3.50159287e-01,  6.49512529e-01,\n",
      "         2.33292431e-01, -6.25756919e-01, -9.34091434e-02,\n",
      "        -8.66747200e-02,  3.41535926e-01,  4.06991243e-01,\n",
      "        -4.17975396e-01, -4.15869467e-02,  8.79274756e-02,\n",
      "        -4.31362122e-01, -9.74333659e-02,  1.40078187e-01,\n",
      "        -2.10768759e-01,  2.45036602e-01, -1.18047267e-01,\n",
      "         3.86048824e-01,  5.58979139e-02, -3.26403707e-01,\n",
      "        -4.70073335e-02, -2.64644116e-01,  5.60076118e-01,\n",
      "         1.09743932e-02,  2.41997898e-01, -2.86900580e-01,\n",
      "         4.54677716e-02, -5.38045228e-01, -1.68555424e-01,\n",
      "        -2.33682215e-01,  2.87959725e-02, -1.99188828e-01,\n",
      "        -2.24730358e-01, -1.22153625e-01,  2.52017409e-01,\n",
      "        -2.99712390e-01, -1.18622154e-01,  3.70908082e-02,\n",
      "        -2.96591580e-01,  3.22893083e-01,  2.39041328e-01,\n",
      "         1.00164413e-01, -3.23887132e-02, -2.30232880e-01,\n",
      "         6.24680780e-02,  2.59408832e-01, -1.17800884e-01,\n",
      "        -2.29000971e-01, -1.16926841e-02, -2.34368593e-02,\n",
      "        -2.59006713e-02,  1.08541377e-01,  5.84438518e-02,\n",
      "         4.34011042e-01, -1.02196738e-01, -3.18959504e-02,\n",
      "         3.86048824e-01,  6.93667531e-02,  5.81974722e-02,\n",
      "         1.22420855e-01, -2.35899642e-01,  3.29545379e-01,\n",
      "        -3.75627168e-02, -3.37490857e-01,  2.81172514e-01,\n",
      "         3.29956025e-01, -1.41864121e-01,  6.70378422e-03,\n",
      "        -2.72968318e-02, -1.27656132e-01,  1.73668161e-01,\n",
      "         6.77242130e-02, -1.88377406e-02, -3.55230302e-01,\n",
      "         1.68494150e-01, -3.02833229e-01, -1.50892488e-03,\n",
      "         9.32657421e-02, -1.50323212e-01, -4.56246644e-01,\n",
      "         4.58784066e-02,  2.30582237e-01, -1.11394972e-01,\n",
      "         1.39913931e-01,  2.75834262e-01, -6.52395487e-02,\n",
      "         2.15142339e-01,  1.88779548e-01, -6.54859319e-02,\n",
      "        -1.71130728e-02,  1.01724826e-01,  1.75885588e-01,\n",
      "        -3.43075514e-01, -8.10079500e-02, -2.43948102e-01,\n",
      "        -1.82106405e-01, -1.14023037e-01, -3.17862481e-01,\n",
      "         2.00441599e-01, -2.02638179e-01, -4.40313965e-01,\n",
      "         1.26691461e-01, -2.11836413e-01,  3.96889597e-01,\n",
      "         5.26128300e-02,  2.09938977e-02,  7.41301253e-02,\n",
      "        -1.36607990e-01, -1.15254946e-01, -1.00389943e-01,\n",
      "        -7.04956800e-02,  2.91244797e-02,  3.31762820e-01,\n",
      "         2.40437493e-01, -1.22564256e-01,  2.36495391e-01,\n",
      "        -1.64366946e-01,  1.32358238e-01, -2.42581293e-02,\n",
      "        -1.23385526e-01, -1.82599157e-01, -2.42880449e-01,\n",
      "        -3.94516401e-02,  1.06980965e-01, -1.66502252e-01,\n",
      "        -1.30859092e-01,  1.32358238e-01, -4.07216758e-01,\n",
      "        -4.13212031e-01,  3.30530912e-01,  2.02494770e-01,\n",
      "         4.48635267e-03,  1.10565200e-02,  2.14485332e-01,\n",
      "         2.13828310e-01, -3.76090586e-01, -5.99834137e-02,\n",
      "        -2.45754898e-01,  9.95895267e-02, -3.18190992e-01,\n",
      "         3.10955308e-02,  2.84129113e-01, -2.23662704e-01,\n",
      "        -2.28179693e-01,  1.58228263e-01, -1.90811872e-01,\n",
      "        -4.91426364e-02, -2.41232291e-03,  3.07206810e-01,\n",
      "        -3.94516401e-02,  7.31445998e-02,  9.58938077e-02,\n",
      "         8.36568698e-02, -6.35442324e-03,  9.65508223e-02,\n",
      "        -2.57170558e-01,  2.65785400e-02,  1.12976238e-01,\n",
      "        -3.30838561e-01, -1.16076216e-01,  1.68165654e-01,\n",
      "        -4.24082167e-02,  5.58157861e-02, -5.12667954e-01,\n",
      "        -2.12575555e-01, -9.31627601e-02, -4.79107313e-02,\n",
      "        -1.19197048e-01, -1.88676566e-01, -4.95532751e-02,\n",
      "        -5.28383590e-02,  1.78730693e-02,  1.02792479e-01,\n",
      "        -6.95101544e-02,  5.20379394e-02, -5.26054680e-01,\n",
      "         2.35104840e-03,  1.61184847e-01,  1.42377734e-01,\n",
      "         1.88040406e-01,  1.02463976e-01, -4.65937614e-01,\n",
      "        -5.69740636e-03, -2.09701106e-01,  2.59901613e-01,\n",
      "        -1.19689807e-01,  2.86839306e-01, -1.13201767e-01,\n",
      "        -1.58700183e-01,  4.71924394e-02, -1.66748628e-01,\n",
      "        -6.56501800e-02,  3.73729765e-01, -1.26588479e-01,\n",
      "         2.50292748e-01, -7.04135522e-02, -5.20170853e-02,\n",
      "        -2.49972735e-02, -2.45262131e-01, -8.90564024e-02,\n",
      "         1.57571256e-01,  4.62069139e-02,  1.29894421e-01,\n",
      "        -2.22049523e-02,  1.48537278e-01,  1.27759114e-01,\n",
      "        -9.59550813e-02,  9.94252712e-02,  3.87362868e-01,\n",
      "        -2.22020164e-01, -2.03705817e-01, -3.72148484e-01,\n",
      "         2.66389638e-01, -2.07483664e-01, -1.26259983e-01,\n",
      "        -6.29399866e-02, -6.17080815e-02,  3.33487481e-01,\n",
      "         5.06124226e-03,  4.05401476e-02, -1.41042858e-01,\n",
      "        -1.62806526e-01,  2.03480303e-01,  2.13224068e-02,\n",
      "         1.28169760e-01,  1.42459869e-01, -5.32489941e-02,\n",
      "         6.04149029e-02, -2.33271584e-01, -1.81695759e-01,\n",
      "        -1.96590126e-02, -1.93686321e-01, -5.89157604e-02,\n",
      "        -1.83743332e-03, -1.47859409e-01, -3.00533652e-01,\n",
      "        -2.09126219e-01, -1.55743599e-01,  4.06580597e-01,\n",
      "        -1.04989059e-01, -4.69252057e-02,  2.62500327e-02,\n",
      "        -1.76932395e-01, -1.07042238e-01,  1.24966793e-01,\n",
      "        -3.56215835e-01,  1.30305052e-01, -2.29329482e-01,\n",
      "        -1.32337376e-01,  5.50766401e-02,  7.09271729e-02,\n",
      "         1.05009913e-01, -3.29636000e-02,  5.50766401e-02,\n",
      "         4.66175526e-02, -2.06990913e-01, -1.04607781e-02,\n",
      "        -2.75484890e-01, -4.32294868e-02,  4.48107533e-02,\n",
      "        -2.56102920e-01, -1.90072730e-01, -1.69130325e-01,\n",
      "         3.47038448e-01, -9.68584791e-02,  1.06159694e-01,\n",
      "         4.52213921e-02,  1.00000158e-01, -8.57713223e-02,\n",
      "        -5.66162020e-02,  1.42706245e-01,  1.89765066e-01,\n",
      "        -1.98367566e-01,  1.76131979e-01, -5.11136875e-02,\n",
      "        -3.31278555e-02, -2.20049113e-01, -4.03521031e-01,\n",
      "         2.40601748e-01,  1.27266347e-01,  2.17852533e-01,\n",
      "         1.70383081e-01,  3.24699879e-01, -4.11763117e-02,\n",
      "         2.69099832e-01, -1.03346519e-01, -6.42540231e-02,\n",
      "         5.23664467e-02,  3.13284218e-01,  6.96131364e-02,\n",
      "         2.22369522e-01,  1.77938774e-01, -3.04997880e-02,\n",
      "        -3.52191597e-01,  6.86276108e-02,  4.62069139e-02,\n",
      "        -4.16989893e-01,  1.10676683e-01,  5.63443363e-01,\n",
      "         1.89190179e-01,  1.95513964e-01, -7.18097165e-02,\n",
      "         3.12597863e-02, -2.46822551e-01, -1.92947179e-01,\n",
      "         1.07966490e-01, -5.17595589e-01, -3.31988335e-01,\n",
      "        -6.40076399e-02, -1.04660556e-01,  3.53661403e-02,\n",
      "        -7.73943588e-02,  7.42943808e-02, -7.55875632e-02,\n",
      "        -2.86079288e-01, -7.74764866e-02,  1.07555851e-01,\n",
      "        -4.97802943e-01,  2.71727920e-01,  5.43374978e-02,\n",
      "         8.75168443e-02,  2.40683869e-01,  6.62459284e-02,\n",
      "        -6.63042665e-01, -2.72364080e-01,  1.81552365e-01,\n",
      "        -2.03952208e-01, -2.59827990e-02, -4.27912772e-01,\n",
      "         3.31516445e-01,  7.61833042e-02, -3.33302379e-01,\n",
      "        -1.65381823e-02, -1.67980537e-01,  4.62069139e-02,\n",
      "         2.84293354e-01, -8.01045522e-02, -1.07124366e-01,\n",
      "         2.52645072e-02, -1.49419814e-01,  1.37667144e-02,\n",
      "        -1.82517037e-01, -1.41699865e-01,  7.54441619e-02,\n",
      "         1.64305672e-01, -2.99248993e-02,  1.15440056e-01,\n",
      "         1.88368917e-01, -6.02591503e-03, -1.60671234e-01,\n",
      "         9.49082822e-02, -2.49122113e-01, -1.62642285e-01,\n",
      "         2.46022135e-01, -4.93614465e-01,  2.14813828e-01,\n",
      "         2.03316048e-01,  9.25265923e-02,  3.83585006e-01,\n",
      "         1.83851928e-01,  1.22913621e-01, -6.54038042e-02,\n",
      "        -1.08520523e-01, -8.44572857e-02, -6.92637786e-02,\n",
      "         2.39123449e-01, -1.62096750e-02, -3.17316949e-02,\n",
      "         9.32657421e-02, -1.76850259e-01, -1.28888041e-01,\n",
      "        -2.16271266e-01,  7.08450451e-02,  4.89171110e-02,\n",
      "         1.13386877e-01, -3.41955088e-02, -3.56210209e-03,\n",
      "         4.32286382e-01, -2.10551731e-02,  2.47171909e-01,\n",
      "         2.74602354e-01, -2.49972735e-02,  4.99055713e-01,\n",
      "         1.15492828e-02,  1.48290887e-01,  3.08849365e-01,\n",
      "         1.48290887e-01,  7.39658698e-02,  6.43570051e-02,\n",
      "         6.60816729e-02,  1.16836213e-01, -1.28231034e-01,\n",
      "        -3.88327539e-01,  4.25880462e-01,  2.71399409e-01,\n",
      "        -3.14002514e-01,  1.57489121e-01,  1.97813526e-01,\n",
      "        -1.09535400e-02, -1.01129085e-01, -9.08631980e-02,\n",
      "         1.68054160e-02,  1.98881179e-01,  8.39853808e-02,\n",
      "         5.94293773e-02,  2.68853456e-01,  6.72314540e-02,\n",
      "        -3.33302379e-01,  3.96150440e-01, -3.96129608e-01,\n",
      "         4.07571718e-03, -2.04444975e-01, -3.48525234e-02,\n",
      "        -3.11568044e-02, -7.59981945e-02,  9.33185127e-03,\n",
      "         2.01591372e-01, -3.23611379e-01,  2.20316350e-01,\n",
      "         8.24249610e-02,  2.62940317e-01,  9.74248629e-03,\n",
      "        -4.53647934e-02,  3.46052915e-01, -2.18652949e-01,\n",
      "         3.41864437e-01,  1.05009913e-01, -2.34257102e-01,\n",
      "         4.43179905e-02, -2.51257420e-01, -2.39348978e-01,\n",
      "        -6.72927275e-02, -1.81613639e-01,  8.96521434e-02,\n",
      "        -7.58339465e-02,  1.35561198e-01,  8.64491910e-02,\n",
      "        -1.54593825e-01, -3.12524229e-01, -1.59357190e-01,\n",
      "         1.05174169e-01,  4.03952539e-01,  1.07063092e-01,\n",
      "        -6.40897676e-02, -2.13396817e-01,  1.28169760e-01,\n",
      "         3.28970492e-01,  3.27380709e-02, -1.77507281e-01,\n",
      "        -1.41124979e-01, -1.86048493e-01,  8.16858187e-02,\n",
      "         1.77281752e-01, -1.96396515e-01,  3.82763743e-01,\n",
      "        -1.29627183e-01,  4.20788586e-01, -7.75058381e-03,\n",
      "        -4.78585213e-01,  1.47716001e-01,  5.86902350e-02,\n",
      "        -2.68861968e-02,  6.04096234e-01, -8.95491689e-02,\n",
      "         8.71883333e-02, -1.96232259e-01, -6.72105998e-02,\n",
      "        -1.64613336e-01,  4.09507826e-02,  2.84381094e-03,\n",
      "        -3.96980233e-02, -1.03675030e-01, -1.66337997e-01,\n",
      "         1.64305672e-01,  1.99127555e-01,  3.55303921e-02,\n",
      "        -2.65547514e-01, -1.89198684e-02, -1.41535610e-01,\n",
      "        -1.23497006e-02,  2.81254649e-01,  3.34390879e-01,\n",
      "         1.03120990e-01, -1.84980854e-01, -2.37624317e-01,\n",
      "        -4.00265306e-02,  3.43096346e-01,  8.20964575e-02,\n",
      "         8.18500742e-02,  3.54594141e-01,  2.16292128e-01,\n",
      "         3.79560769e-01, -2.06005380e-01, -3.29688787e-01,\n",
      "         1.77035376e-01, -1.26259983e-01,  1.21928096e-01,\n",
      "        -1.60835490e-01,  2.26364397e-02,  3.22400331e-01,\n",
      "        -4.87320013e-02,  5.69655634e-02,  1.28339627e-03,\n",
      "        -3.77486765e-01, -1.82927668e-01, -1.01293340e-01,\n",
      "        -3.53341371e-01,  1.40653074e-01, -4.48855191e-01,\n",
      "        -1.29462928e-01,  6.53953012e-03, -3.32973868e-01,\n",
      "        -1.20593205e-01,  2.36659646e-01, -2.28343949e-01,\n",
      "        -3.32645357e-01,  1.34329289e-01,  1.42594771e-02,\n",
      "         1.30140796e-01,  6.75599575e-02, -1.43588796e-01,\n",
      "         7.08450451e-02,  1.76296234e-01, -1.00882709e-01,\n",
      "        -5.09494357e-02, -5.23399794e-04, -3.48525234e-02,\n",
      "        -6.76505873e-03, -2.73021102e-01, -8.21577311e-02,\n",
      "        -1.42192632e-01,  1.32933125e-01,  6.62165694e-03,\n",
      "         1.23817019e-01,  1.69479683e-01,  1.49933428e-01,\n",
      "         1.52315125e-01,  5.65549284e-02, -9.61193368e-02,\n",
      "         1.28005505e-01, -1.38279889e-02, -7.03314245e-02,\n",
      "         2.41258755e-01,  6.18110634e-02,  2.73176841e-02,\n",
      "        -2.42634073e-01, -2.27029920e-01,  6.74561322e-01,\n",
      "         1.19300030e-01,  1.47522390e-02, -2.68339843e-01,\n",
      "         2.01591372e-01,  6.73957020e-02,  8.18500742e-02,\n",
      "         1.24474034e-01,  1.70629457e-01,  1.37121603e-01,\n",
      "         2.18591675e-01, -3.35027039e-01, -6.87710121e-02,\n",
      "        -5.21813408e-02, -3.54737550e-01, -1.89169332e-01,\n",
      "         2.53906339e-01,  2.95351166e-02,  1.23652764e-01,\n",
      "        -1.71101376e-01, -8.40466544e-02, -3.58380489e-02,\n",
      "         8.83381143e-02, -4.65691239e-01, -1.55086592e-01,\n",
      "         2.69346237e-01, -2.14875102e-01, -1.78164303e-01,\n",
      "        -3.04804265e-01,  5.12166694e-02, -1.02278866e-01,\n",
      "         2.40326002e-02, -1.04660556e-01,  4.41537388e-02,\n",
      "         2.72220671e-01, -9.64478403e-02, -3.39708298e-01,\n",
      "        -2.42716193e-01,  7.88934976e-02, -1.76879615e-02,\n",
      "         1.28251880e-01, -2.54900362e-02,  6.54246584e-02,\n",
      "        -1.47366643e-01, -1.40303716e-01,  7.99611509e-02,\n",
      "         2.69838989e-01, -2.61441171e-01, -6.02591503e-03,\n",
      "        -3.88409644e-01,  1.35203330e-02, -4.57396418e-01,\n",
      "         7.87292421e-02, -9.61193368e-02, -1.28805920e-01,\n",
      "         1.65619701e-01, -2.79538482e-02,  1.34165034e-01,\n",
      "        -1.49994701e-01, -3.15146684e-03, -9.57086980e-02,\n",
      "         1.90668464e-01, -2.41155773e-01,  1.92064628e-01,\n",
      "        -1.67405650e-01, -2.56431431e-01, -1.61492497e-01,\n",
      "        -6.08046837e-02, -4.95826267e-03,  1.14290275e-01,\n",
      "        -3.01712807e-02, -2.16928288e-01, -4.94711474e-02,\n",
      "        -1.33979917e-01,  1.98142037e-01,  1.75146446e-01,\n",
      "        -2.39020467e-01,  1.33754402e-01,  1.29155278e-01,\n",
      "         5.91941416e-01, -7.24667311e-02,  2.11446628e-01,\n",
      "        -7.93654099e-02,  1.76542610e-01,  2.21794635e-01,\n",
      "         9.84397456e-02, -4.49541546e-02,  1.44759431e-01,\n",
      "        -3.02258343e-01, -2.64562011e-01,  9.19517055e-02,\n",
      "        -2.17995942e-01,  2.42326409e-01, -1.58207417e-01,\n",
      "        -7.65730888e-02,  1.28908902e-01,  1.99456066e-01,\n",
      "        -5.71089648e-02, -1.72773264e-02,  1.26116574e-01,\n",
      "        -2.05266237e-01, -6.92637786e-02, -1.96068004e-01,\n",
      "         2.11693004e-01,  1.95267588e-01,  1.90750599e-01,\n",
      "        -2.73789596e-02,  1.84479579e-02,  1.57377645e-02,\n",
      "         6.71493262e-02,  3.39699797e-02,  2.95955390e-01,\n",
      "         2.72056431e-01,  2.24669084e-01,  2.73176841e-02,\n",
      "         3.07124674e-01,  3.18346731e-02, -6.09689392e-02,\n",
      "         2.54809737e-01,  1.77856639e-01,  1.75310701e-01,\n",
      "         4.19720918e-01,  1.47387490e-01, -1.77507281e-01,\n",
      "         2.33374551e-01,  1.63812906e-01, -2.22841442e-01,\n",
      "         2.00605854e-01,  4.41238225e-01,  2.22123146e-01,\n",
      "        -1.79067701e-01,  2.31732011e-01, -3.60844322e-02,\n",
      "        -6.39255121e-02, -7.09356694e-03,  4.62890416e-02,\n",
      "        -1.20839588e-01, -1.86048493e-01, -8.22398588e-02,\n",
      "        -3.80607575e-01, -2.36638784e-01, -1.69488173e-02,\n",
      "         3.67623009e-02, -9.62014645e-02, -4.15511608e-01,\n",
      "        -8.06794390e-02,  2.81829536e-01,  3.28559846e-01,\n",
      "         1.62581012e-01, -1.82188526e-01,  1.02710351e-01,\n",
      "         5.33549070e-01, -2.74745762e-01,  7.85649866e-02,\n",
      "        -1.98039055e-01, -1.74304321e-01,  3.84048410e-02,\n",
      "         2.12678537e-01,  8.49708989e-02,  3.34473014e-01,\n",
      "         2.23272920e-01,  4.82466012e-01, -6.09689392e-02,\n",
      "        -2.70064503e-01, -8.16121977e-03,  1.92803770e-01,\n",
      "        -1.47530898e-01,  1.69890314e-01, -8.13364610e-02,\n",
      "         1.76131979e-01,  4.66175526e-02, -4.71686512e-01,\n",
      "         1.51001081e-01, -2.73760229e-01,  2.17770413e-01,\n",
      "        -1.04989059e-01,  3.59410271e-02, -5.46451546e-02,\n",
      "         3.85227561e-01, -3.66892368e-01,  2.92013288e-01,\n",
      "        -7.65730888e-02,  5.53259552e-01,  2.57273555e-01,\n",
      "         4.99548465e-01,  3.15583766e-01,  1.41638592e-01,\n",
      "        -5.45600891e-01, -8.24334659e-03,  1.84016168e-01,\n",
      "        -4.69252057e-02, -1.70280099e-01,  9.39227566e-02,\n",
      "        -3.95144075e-01,  1.18777910e-02,  6.15646802e-02,\n",
      "        -2.12247044e-01,  2.39287704e-01,  9.18695778e-02,\n",
      "        -2.10275993e-01,  3.83338630e-01,  2.50046343e-01,\n",
      "        -1.34994807e-02, -1.92483775e-02,  1.17739610e-01,\n",
      "        -1.89169332e-01,  3.30665819e-02, -1.51965752e-01,\n",
      "        -1.28148898e-01, -2.91089058e-01,  1.50097683e-01,\n",
      "         1.62909508e-01,  1.54913832e-02,  2.06190497e-01,\n",
      "         4.66996767e-02, -2.70393014e-01, -2.99219638e-01,\n",
      "         2.46925533e-01,  6.59995452e-02, -8.83993879e-02,\n",
      "         1.58146143e-01, -2.28015438e-01, -1.87198281e-01,\n",
      "        -5.79302385e-02,  1.92557395e-01, -5.92442714e-02,\n",
      "        -3.53177130e-01,  4.30860855e-02,  9.85218734e-02,\n",
      "         3.26917320e-01, -9.58729535e-02, -1.43424541e-01,\n",
      "         1.01478450e-01, -1.67317910e-03, -1.92290157e-01,\n",
      "         4.17720526e-02,  5.87723590e-02,  1.90914854e-01,\n",
      "         3.42603594e-01, -1.31187603e-01, -5.33311181e-02,\n",
      "         1.19628534e-01,  2.64007956e-01, -1.61410376e-01,\n",
      "        -2.56542899e-02, -2.57334828e-01, -2.84847379e-01,\n",
      "        -2.65876025e-01, -2.30807766e-01, -1.66420132e-01,\n",
      "        -3.78912278e-02,  4.63987440e-01,  2.22698033e-01,\n",
      "         8.16036910e-02, -9.11095813e-02,  1.36136085e-01,\n",
      "        -2.97905594e-01,  2.39205584e-01,  8.05360377e-02,\n",
      "         5.43322206e-01,  1.71204343e-01, -2.09701106e-01,\n",
      "        -1.76850259e-01,  1.36053950e-01, -2.07894310e-01,\n",
      "        -4.18632418e-01,  3.18786740e-01,  2.11364493e-01,\n",
      "         5.82795963e-02,  1.75721332e-01,  2.07668781e-01,\n",
      "         1.28498256e-01, -4.17511985e-02,  2.15470850e-01,\n",
      "        -3.03490251e-01, -8.56070668e-02, -6.34327531e-02,\n",
      "         3.65159176e-02,  4.17720526e-02, -2.42581293e-02,\n",
      "         8.57100487e-02, -1.99763730e-01,  4.02116366e-02,\n",
      "        -1.54758081e-01, -7.60803223e-02,  4.96017009e-01,\n",
      "        -2.86900580e-01,  1.13850283e-02, -2.40170255e-01,\n",
      "        -1.15665585e-01, -1.04167789e-01, -1.39922425e-02,\n",
      "        -2.42798313e-01,  9.65508223e-02, -8.95491689e-02,\n",
      "         3.88019860e-01,  1.79827690e-01, -1.80792361e-01,\n",
      "         3.28201987e-02, -3.27881992e-01,  2.55877376e-01,\n",
      "        -9.39312577e-03,  2.23519310e-01,  8.01254064e-02,\n",
      "        -5.85872531e-02, -8.17470923e-02, -1.44574314e-01,\n",
      "         3.10902536e-01,  1.83851928e-01,  2.39287704e-01,\n",
      "         1.27348483e-01,  1.98634803e-01,  1.58198923e-02,\n",
      "         9.21159610e-02,  7.53620341e-02,  1.83523417e-01,\n",
      "        -2.70504504e-02,  5.25418520e-01, -2.51421660e-01,\n",
      "        -1.75530615e-03, -1.05974585e-01, -1.39071807e-01,\n",
      "         2.72056431e-01, -2.01899022e-01,  1.31454840e-01,\n",
      "         2.31814146e-01, -6.58965632e-02,  1.86397865e-01,\n",
      "        -1.37429267e-01, -1.00800581e-01,  9.15410668e-02,\n",
      "        -2.45837018e-01,  1.84016168e-01, -1.29791439e-01,\n",
      "         2.65785400e-02, -1.54840201e-01, -5.70268370e-02,\n",
      "         8.58743042e-02, -1.28805920e-01,  2.37316653e-01,\n",
      "         2.79365718e-01, -2.30397135e-01,  1.39309680e-02,\n",
      "        -1.07071595e-02,  1.17657483e-01,  3.16076547e-01,\n",
      "        -2.29575858e-01, -1.35458216e-01, -3.14853117e-02,\n",
      "         1.80156201e-01,  3.84048410e-02, -1.00718454e-01,\n",
      "         3.84869687e-02, -3.70505959e-01,  9.24972445e-03,\n",
      "         2.67210931e-01,  1.16314096e-02, -2.37131551e-01,\n",
      "        -3.76829743e-01,  1.00657180e-01,  4.89171110e-02,\n",
      "        -3.06372567e-05, -4.66788262e-02, -1.43207517e-02,\n",
      "        -4.12584357e-02,  1.84098303e-01, -1.83584690e-01,\n",
      "        -1.33569285e-01,  1.08101387e-02,  1.48537278e-01,\n",
      "         1.77528128e-01, -4.55290452e-02, -3.23282868e-01,\n",
      "        -2.37377927e-01, -1.05071187e-01,  1.77856639e-01,\n",
      "        -7.10705742e-02,  1.22092351e-01,  2.64142863e-02,\n",
      "        -3.98839802e-01, -1.31598234e-01,  1.56010836e-01,\n",
      "        -2.85011649e-01, -1.72004774e-01,  2.08654299e-01,\n",
      "        -1.89198684e-02,  6.99416474e-02, -1.62313774e-01,\n",
      "        -1.93111435e-01,  2.04876453e-01,  2.10543230e-01,\n",
      "         2.22205266e-01,  1.48126632e-01, -2.85340160e-01,\n",
      "        -6.84425011e-02,  2.88235456e-01,  1.98716924e-01,\n",
      "        -1.29627183e-01, -4.01714236e-01,  1.47522390e-02,\n",
      "        -3.38640630e-01, -1.35211825e-01,  2.19659328e-01,\n",
      "         1.31947592e-01,  1.76788986e-01,  6.12361729e-02,\n",
      "        -1.49748325e-01, -2.61194795e-01, -3.52684379e-01,\n",
      "        -4.79817092e-01,  9.38406289e-02, -9.87474024e-02,\n",
      "        -5.86992979e-01,  2.94066489e-01,  5.92762709e-01,\n",
      "         7.84828588e-02,  9.26908478e-02,  2.65814751e-01,\n",
      "         4.63711694e-02,  2.27185674e-02, -9.39312577e-03,\n",
      "        -1.02525249e-01, -2.06005380e-01, -1.72661781e-01,\n",
      "        -1.97382033e-01, -4.86498773e-02,  1.41967103e-01,\n",
      "        -2.47561693e-01, -3.19505036e-01,  3.23550105e-01,\n",
      "        -2.79673398e-01, -4.49541546e-02, -3.39491256e-02,\n",
      "         3.83585006e-01],\n",
      "       [-4.40553516e-01,  6.08321093e-02,  2.00781250e+00,\n",
      "         9.53642547e-01,  1.54987741e-02, -1.03595221e+00,\n",
      "        -9.05756116e-01,  1.52858257e-01,  1.97999549e+00,\n",
      "        -4.32814956e-01, -4.93834555e-01, -4.99743044e-01,\n",
      "        -8.28631938e-01,  2.47760206e-01, -6.95350885e-01,\n",
      "         6.00596786e-01,  4.40701395e-01, -5.76344371e-01,\n",
      "         6.52570665e-01, -1.20954692e+00,  8.28361511e-01,\n",
      "        -1.62356007e+00,  9.58348453e-01,  1.07343340e+00,\n",
      "         1.91589054e-02,  1.18945956e+00,  3.23211193e-01,\n",
      "        -1.95694566e+00,  1.24153805e+00, -1.16091955e+00,\n",
      "         8.61093521e-01,  8.76413822e-01,  1.06036150e+00,\n",
      "        -8.96515548e-02,  6.09799445e-01,  2.63237327e-01,\n",
      "         1.10104132e+00,  6.10008597e-01, -1.70382154e+00,\n",
      "         1.40347220e-02, -1.90429211e+00,  6.91786349e-01,\n",
      "        -5.51417470e-02,  1.19202161e+00,  9.77119684e-01,\n",
      "         1.52263606e+00, -3.56788814e-01,  3.14531446e-01,\n",
      "         4.05041248e-01,  3.23158920e-01, -4.76004481e-01,\n",
      "         2.87028193e-01, -7.43350923e-01, -5.21756113e-01,\n",
      "        -1.60337698e+00,  6.79812491e-01, -6.81285560e-01,\n",
      "         9.87524927e-01, -2.29677692e-01,  5.48884392e-01,\n",
      "        -1.45508945e+00,  7.03080475e-01, -7.48318195e-01,\n",
      "        -1.98371696e+00, -2.21939132e-01,  5.01093566e-01,\n",
      "        -7.12344348e-01, -7.62697279e-01, -1.61965281e-01,\n",
      "        -1.72004491e-01,  3.56518388e-01,  6.10322297e-01,\n",
      "        -3.69651556e-01,  5.91028214e-01, -7.14592755e-01,\n",
      "        -1.74000454e+00, -2.37311676e-01, -1.38491952e+00,\n",
      "        -2.16082931e-01, -1.45085418e+00, -1.44501224e-01,\n",
      "         3.14426869e-01, -1.29200447e+00,  4.66845185e-01,\n",
      "        -3.14749599e-01, -6.33651555e-01, -9.52187479e-01,\n",
      "         2.74949759e-01,  1.88284516e+00,  3.81511837e-01,\n",
      "        -4.63051461e-02,  2.96126217e-01, -1.62017569e-01,\n",
      "         6.36936665e-01, -1.07888031e+00, -3.11417487e-02,\n",
      "         1.77799433e-01, -8.90017569e-01, -6.01651549e-01,\n",
      "        -1.25472343e+00, -4.73180950e-01, -1.74711561e+00,\n",
      "        -1.52599144e+00, -1.82962537e+00, -5.41625824e-03,\n",
      "        -8.17180991e-01,  7.97459543e-01, -1.75516784e+00,\n",
      "        -7.85808444e-01, -1.92553520e-01,  1.39024389e+00,\n",
      "         5.28910518e-01, -3.44867229e-01,  5.46897471e-01,\n",
      "         6.44256949e-01, -8.34436249e-03,  4.75629479e-01,\n",
      "         8.50165427e-01,  5.78792870e-01,  1.25032234e+00,\n",
      "        -4.29064557e-02, -3.80527377e-01, -6.60698563e-02,\n",
      "         1.48870134e+00, -6.94252849e-01, -1.21399140e+00,\n",
      "        -3.01677704e-01, -5.61285555e-01,  7.73145854e-01,\n",
      "        -1.43455476e-01, -2.88933832e-02, -6.66017592e-01,\n",
      "         5.96988976e-01,  1.00959027e+00,  1.72884390e-01,\n",
      "        -1.90828025e-01,  2.20152363e-01, -1.50305152e-01,\n",
      "        -5.58200598e-01, -9.25468564e-01, -4.11809646e-02,\n",
      "         1.32185173e+00, -1.29953396e+00,  7.36425668e-02,\n",
      "         3.56204659e-01, -3.57939124e-01,  3.23734075e-01,\n",
      "        -2.68736511e-01,  7.06374586e-01,  1.43289626e-01,\n",
      "         5.24466097e-01, -4.75377053e-01,  5.47368050e-01,\n",
      "        -1.87600446e+00, -7.93651581e-01, -8.88292074e-01,\n",
      "         9.18909311e-02,  4.03002053e-01, -7.84030616e-01,\n",
      "        -7.75873780e-01, -7.91246295e-01, -7.45337844e-01,\n",
      "        -1.96306336e+00,  1.78270012e-01, -4.44527358e-01,\n",
      "        -3.19089472e-01,  1.86426878e-01, -3.01207095e-01,\n",
      "        -1.16473651e+00,  3.72832119e-01, -1.52030632e-01,\n",
      "        -9.96109068e-01,  3.46374601e-01, -7.14801908e-01,\n",
      "        -5.33782244e-01,  2.63745915e-02, -3.81482840e-02,\n",
      "         6.77250385e-01,  1.14792891e-01, -5.52463233e-02,\n",
      "         3.22374582e-01,  6.36033490e-02,  4.13198113e-01,\n",
      "        -1.80557311e+00, -5.27560055e-01, -1.50240970e+00,\n",
      "        -1.87145543e+00, -5.24370492e-01, -4.73546982e-01,\n",
      "        -1.31025290e+00, -3.98043722e-01, -3.45599264e-01,\n",
      "         9.15106595e-01, -9.44187522e-01, -8.99129882e-02,\n",
      "         1.36870134e+00,  2.35510617e-02,  6.21093571e-01,\n",
      "         2.38348454e-01, -1.04823983e+00,  5.37799418e-01,\n",
      "        -1.10225284e+00, -9.87481594e-01, -8.56553495e-01,\n",
      "        -8.71037185e-01, -9.98999178e-02, -6.12422824e-01,\n",
      "        -1.23851430e+00,  1.29732883e+00,  5.77015102e-01,\n",
      "         1.33982435e-01, -4.89756137e-01,  2.68831709e-03,\n",
      "         9.77799416e-01, -7.64788806e-01,  3.55054319e-01,\n",
      "        -8.23141754e-01, -2.00239792e-01, -7.75664628e-01,\n",
      "        -1.73207104e-01,  1.30093670e+00,  1.74778640e+00,\n",
      "        -8.09233248e-01,  2.12675244e-01, -1.72614825e+00,\n",
      "        -2.46058013e-02, -2.37573117e-01, -1.40631944e-01,\n",
      "         1.18538117e+00,  8.52779806e-01, -1.96630514e+00,\n",
      "        -3.43312919e-02, -1.38512862e+00,  9.65445265e-02,\n",
      "        -1.84677577e+00,  2.16962829e-01,  5.97863570e-02,\n",
      "        -6.92579687e-01,  9.97511864e-01,  1.61537990e-01,\n",
      "         3.41354996e-01,  2.23551065e-01, -5.46279013e-01,\n",
      "        -9.21233237e-01, -1.06801882e-01,  1.06109357e+00,\n",
      "         3.79943222e-01,  2.30804738e-02,  1.13921118e+00,\n",
      "         3.77642572e-01,  1.35289624e-01, -4.53311682e-01,\n",
      "         1.57354981e-01, -5.48945665e-01, -1.41336393e+00,\n",
      "         2.79185057e-01, -2.72553504e-01, -3.37233245e-01,\n",
      "         5.96204638e-01,  2.78609872e-01, -2.25756124e-01,\n",
      "        -1.22099793e+00, -6.43429339e-01,  1.48598242e+00,\n",
      "        -1.24667120e+00,  8.89537990e-01,  5.32361507e-01,\n",
      "        -7.37128675e-01, -4.76893395e-01,  2.45093539e-01,\n",
      "        -7.01259375e-01, -5.93494713e-01, -1.10618874e-01,\n",
      "        -4.99377042e-01, -2.36736521e-01, -9.78435874e-01,\n",
      "        -3.41886848e-01,  6.78871334e-01, -6.07926071e-01,\n",
      "         4.29459572e-01,  6.52779818e-01, -1.09540319e+00,\n",
      "        -6.45573139e-01, -9.08018798e-02,  4.54400748e-01,\n",
      "         6.69564128e-01,  3.73773277e-01,  2.51943231e-01,\n",
      "        -1.13651551e-01, -5.65363944e-01, -9.21390116e-01,\n",
      "        -1.25278878e+00,  8.77877831e-01,  4.92936671e-01,\n",
      "         2.07760215e-01,  1.09942031e+00,  8.83263469e-01,\n",
      "         8.32126200e-01,  9.64518368e-01,  3.75603348e-01,\n",
      "         9.94897485e-01, -4.93886858e-01,  2.22609892e-01,\n",
      "         4.78505313e-01,  6.99054301e-01, -5.81730008e-01,\n",
      "        -1.83375609e+00,  2.24910542e-01,  1.81250408e-01,\n",
      "         5.90139270e-01,  1.02694976e+00, -2.10226715e-01,\n",
      "        -1.28128552e+00,  4.82426882e-01, -3.69494677e-01,\n",
      "         1.23211190e-01,  1.43812507e-01,  1.39996934e+00,\n",
      "        -9.43560064e-01, -7.02357411e-01,  2.13093549e-01,\n",
      "         6.79394186e-01, -1.75455481e-01,  4.79028195e-01,\n",
      "         1.34151185e+00, -1.09102532e-01, -6.63821459e-01,\n",
      "        -1.26357436e-01,  5.67551076e-01, -1.48259270e+00,\n",
      "        -4.87141758e-01,  1.00200856e+00, -6.61468565e-01,\n",
      "        -2.48658091e-01, -7.46488154e-01, -6.20318234e-01,\n",
      "         1.89564139e-01,  8.48387659e-01,  6.09328866e-01,\n",
      "         1.15908051e+00,  6.90935478e-02,  2.76727527e-01,\n",
      "        -3.69979590e-02, -6.20057201e-03,  7.57863596e-02,\n",
      "         1.16413809e-01,  5.63786328e-01, -2.89494693e-01,\n",
      "         7.22688317e-01, -8.56187522e-01, -4.52945679e-01,\n",
      "        -4.87978339e-01, -8.84841084e-01, -7.31533885e-01,\n",
      "         1.43902814e+00, -7.76919544e-01, -1.24573004e+00,\n",
      "        -1.52658090e-01, -1.33050248e-01, -1.27799141e+00,\n",
      "        -3.43350887e-01,  9.98505294e-01,  4.17224258e-01,\n",
      "        -1.95377037e-01,  5.68230808e-01, -1.02200575e-01,\n",
      "        -7.06122160e-01,  1.10773408e+00, -1.76463199e+00,\n",
      "        -4.84213650e-01,  8.08753669e-01, -8.31716895e-01,\n",
      "        -4.18854177e-01, -4.28475082e-01,  1.46897465e-01,\n",
      "         1.15681782e-01,  3.77224267e-01, -2.16814950e-01,\n",
      "         6.52779818e-01, -9.02095973e-01,  1.46208704e+00,\n",
      "         1.17806089e+00, -1.30941629e+00,  1.93544650e+00,\n",
      "        -1.13655353e+00,  1.19976020e+00,  1.13210011e+00,\n",
      "         6.32649124e-01, -1.79872346e+00,  1.06165439e-01,\n",
      "        -1.23899922e-01,  9.13642585e-01, -9.73207116e-01,\n",
      "        -9.65573132e-01,  1.87002048e-01,  7.50871301e-01,\n",
      "         1.63577199e-01,  7.71458298e-02, -1.26784766e+00,\n",
      "         1.03343344e+00, -1.23276269e+00,  1.07002042e-01,\n",
      "        -3.13442409e-01,  1.74714461e-01, -4.52422798e-01,\n",
      "        -7.26514280e-01, -1.07710254e+00,  1.24723732e+00,\n",
      "        -4.39403176e-01,  8.98113132e-01, -1.50722015e+00,\n",
      "        -6.65546954e-01,  1.96518376e-01, -9.98671174e-01,\n",
      "         8.62766743e-01,  3.72518390e-01, -3.52762669e-01,\n",
      "        -7.05442429e-01, -2.34645009e-01,  2.85982430e-01,\n",
      "         1.72603476e+00, -2.96344370e-01,  9.26819026e-01,\n",
      "        -1.03037171e-01, -6.16658092e-01,  9.70479190e-01,\n",
      "         2.53930151e-01, -1.98566586e-01,  1.23317194e+00,\n",
      "        -5.52030623e-01,  9.12439942e-01, -2.14880317e-01,\n",
      "        -5.34671187e-01,  6.57015085e-01, -5.75560033e-01,\n",
      "         1.03108048e+00, -1.77979529e+00, -2.84750815e-02,\n",
      "        -4.13886845e-01,  4.20413822e-01, -7.75403202e-01,\n",
      "         5.23092337e-02, -1.32991302e+00, -1.22047508e+00,\n",
      "         4.10674028e-02,  2.36556381e-02,  4.92570668e-01,\n",
      "        -2.46671155e-01, -5.07795334e-01, -8.29248384e-05,\n",
      "         7.07211196e-01, -9.14540470e-01,  4.42479163e-01,\n",
      "         2.54819036e-01, -3.19194049e-01, -4.67690766e-01,\n",
      "         1.12701386e-01, -1.07286727e+00, -9.90633145e-02,\n",
      "         6.00178540e-01,  1.87472627e-01, -1.20396651e-01,\n",
      "        -1.89573124e-01,  3.70270014e-01, -1.97520837e-01,\n",
      "        -5.42671144e-01, -9.79652777e-02, -1.08593917e+00,\n",
      "        -1.40353394e+00, -4.85573113e-01,  3.20335388e-01,\n",
      "        -2.55298615e-01,  8.15551043e-01,  1.87610006e+00,\n",
      "         1.11446485e-01,  6.87132776e-01,  5.65720975e-01,\n",
      "        -7.01782286e-01, -6.85625434e-01, -2.69939125e-01,\n",
      "        -1.13561237e+00, -7.78435886e-01,  4.98897070e-03,\n",
      "         1.76073939e-01,  3.54726315e-02, -8.57299864e-02,\n",
      "         5.48190363e-02,  1.60701394e-01,  8.08335364e-01,\n",
      "         1.12159026e+00, -1.55187380e+00, -5.40161371e-01,\n",
      "         9.08413827e-01,  3.01825583e-01, -2.51115590e-01,\n",
      "        -9.08945680e-01, -1.13482797e+00,  4.56858248e-01,\n",
      "        -1.85808420e-01,  2.74845183e-01,  1.61711967e+00,\n",
      "         1.44535494e+00,  1.42348453e-01, -3.73625398e-01,\n",
      "        -8.35690796e-01, -1.19705021e+00,  1.93596935e+00,\n",
      "         3.50609899e-01, -1.48243582e+00, -2.15037167e-01,\n",
      "        -3.32370520e-01, -1.10162544e+00, -1.13233253e-01,\n",
      "        -1.09848821e+00, -1.25064504e+00, -1.13546975e-01,\n",
      "        -5.53912997e-01,  5.96813741e-04, -6.09390140e-01,\n",
      "         1.10087007e-01,  6.95498765e-01, -2.84841090e-01,\n",
      "         1.91254449e+00,  3.72518390e-01, -1.31272465e-01,\n",
      "        -6.21416271e-01,  4.05616432e-01,  2.07446486e-01,\n",
      "        -3.28762650e-01, -2.10069850e-01, -2.97337830e-01,\n",
      "         4.78139311e-01,  8.01262259e-02, -5.30017555e-01,\n",
      "        -6.50958717e-01, -8.37207079e-01, -1.50775731e-01,\n",
      "         1.69067398e-01,  1.05738115e+00,  7.08570659e-01,\n",
      "         3.97982448e-01,  3.41616422e-01,  1.06553805e+00,\n",
      "         8.85825139e-03,  1.50396931e+00, -1.39637053e+00,\n",
      "        -1.55952200e-01, -1.18220055e+00,  1.03479290e+00,\n",
      "        -4.24030632e-01,  4.09224272e-01,  7.14464858e-02,\n",
      "        -9.57677722e-01,  2.51002043e-01,  1.61785173e+00,\n",
      "         2.33694851e-01,  5.72152376e-01,  2.37041265e-01,\n",
      "        -1.37101102e+00, -5.10148287e-01,  5.36164232e-02,\n",
      "         3.73549834e-02,  1.10453025e-01, -8.96515548e-02,\n",
      "         4.52504084e-02, -1.74514294e-01, -3.80579650e-01,\n",
      "         5.30113161e-01, -1.47516787e+00,  5.73720992e-01,\n",
      "         4.63028193e-01,  3.81041259e-01, -3.96370500e-01,\n",
      "        -1.69325936e+00, -1.20128548e+00,  3.62426877e-01,\n",
      "        -6.62461996e-01,  6.35943234e-01, -3.63377035e-01,\n",
      "         6.38766766e-01,  1.24802160e+00, -1.31795347e-01,\n",
      "        -1.99873775e-01,  4.74636018e-01, -4.46200579e-01,\n",
      "        -4.42540437e-01, -4.69886839e-01,  9.09459531e-01,\n",
      "         3.99394214e-01,  6.44399524e-02, -1.40076268e+00,\n",
      "        -1.92384768e+00, -2.92736530e-01, -3.79272461e-01,\n",
      "         3.87368053e-01,  3.54008585e-01,  3.82662177e-01,\n",
      "         6.61773264e-01, -9.24227908e-02, -4.34540451e-01,\n",
      "        -7.60710359e-01, -8.35339054e-02,  1.14161646e+00,\n",
      "         7.53157660e-02,  7.15995491e-01, -3.96841109e-01,\n",
      "         9.88884389e-01,  8.74165416e-01,  1.28106737e+00,\n",
      "         1.27353799e+00, -2.50383586e-01,  3.99969369e-01,\n",
      "         4.26688313e-01, -3.77703846e-01, -1.21122015e+00,\n",
      "        -1.64265931e-01, -9.64945674e-01,  2.04138067e-02,\n",
      "         6.58374608e-01,  1.69670141e+00,  4.99472618e-01,\n",
      "         1.33026959e-02, -1.27403185e-01,  3.37485701e-01,\n",
      "        -1.60081494e+00, -7.49729991e-01, -2.79716909e-01,\n",
      "         1.11060989e+00, -1.51507765e-01, -2.63350904e-01,\n",
      "         1.57407269e-01, -3.41573119e-01,  9.76387680e-01,\n",
      "         6.37407243e-01, -1.02047503e+00, -9.40161347e-01,\n",
      "         1.01354986e-01, -3.60971808e-01,  3.57721001e-01,\n",
      "         1.01100206e+00,  3.10804732e-02,  1.80100083e-01,\n",
      "         9.26400721e-01,  6.78086996e-01, -6.36788785e-01,\n",
      "        -1.82010901e+00, -2.54409730e-01, -7.59612322e-01,\n",
      "        -1.74462005e-01,  2.38766745e-01,  6.77773297e-01,\n",
      "         1.00361519e-01, -1.22612214e+00,  2.36675248e-01,\n",
      "         7.36948550e-02, -3.27141762e-01, -5.02775729e-01,\n",
      "        -5.12814939e-01, -1.11255348e+00, -5.03821492e-01,\n",
      "         9.21224236e-01,  4.96387661e-01, -7.68082917e-01,\n",
      "         7.69171953e-01,  3.83812487e-01,  4.23080474e-01,\n",
      "         1.21171974e-01, -3.79272461e-01, -6.40239775e-01,\n",
      "         1.08948565e+00, -6.41546965e-01, -5.32684207e-01,\n",
      "         6.39185071e-01, -7.61651576e-01, -2.67495923e-02,\n",
      "         6.48021638e-01,  3.26139301e-01,  5.21000810e-02,\n",
      "        -6.15716934e-01, -1.33195221e+00, -2.30932593e-01,\n",
      "         3.03028196e-01,  3.51132751e-01, -4.37311679e-01,\n",
      "         5.19341886e-01, -5.19926071e-01, -3.06711607e-02,\n",
      "         7.35028207e-01, -7.09677696e-01, -4.60631937e-01,\n",
      "        -7.58880317e-01, -1.39952213e-01, -8.53886843e-01,\n",
      "        -1.27793908e+00, -1.29686725e+00,  4.28974666e-02,\n",
      "         6.57590270e-01, -9.09416258e-01,  8.85145843e-01,\n",
      "        -1.81677699e-01, -1.41514170e+00,  4.56962824e-01,\n",
      "        -5.27194023e-01,  1.55364251e+00, -2.09494695e-01,\n",
      "        -3.05703849e-01, -4.64971811e-01,  2.93720990e-01,\n",
      "        -1.27089456e-01,  1.12111932e-02,  3.00204242e-03,\n",
      "         4.45183814e-02,  2.71132767e-01, -3.69599253e-01,\n",
      "         1.85067400e-01, -1.33252740e+00, -9.33154821e-01,\n",
      "        -7.88004518e-01,  5.69851696e-01, -4.42136452e-02,\n",
      "         1.26062298e+00,  5.79577208e-01,  6.13302708e-01,\n",
      "        -7.96422780e-01,  4.86296147e-01, -2.93520838e-01,\n",
      "        -1.07167892e-01,  3.95510606e-02,  6.67995512e-01,\n",
      "        -8.58174443e-01,  1.49198115e-01, -4.70409721e-01,\n",
      "         4.85250413e-01,  1.95054337e-01,  2.58270025e-01,\n",
      "        -1.87114179e+00,  7.78531432e-01,  3.14008564e-01,\n",
      "         4.10636038e-01, -9.03664649e-01,  9.92178500e-01,\n",
      "        -4.94043708e-01,  5.42453051e-01, -5.46749592e-01,\n",
      "         3.56152356e-01, -6.06305122e-01,  5.05171955e-01,\n",
      "        -1.08369076e+00,  1.13298893e+00, -1.04714179e+00,\n",
      "         4.03420329e-01,  1.07113278e+00, -5.63220203e-01,\n",
      "         3.33825558e-01, -2.01494694e-01,  4.32439953e-01,\n",
      "        -7.56893396e-01,  1.40570670e-01, -6.82383597e-01,\n",
      "         1.50229621e+00,  6.72439933e-01, -8.23507786e-01,\n",
      "        -1.84814945e-01,  6.58060849e-01, -1.48139012e+00,\n",
      "        -4.64501232e-01,  1.37178636e+00,  2.93616414e-01,\n",
      "         4.58792895e-01,  9.89145815e-01,  1.99237332e-01,\n",
      "         1.56727538e-01, -1.03971696e+00,  5.69119692e-01,\n",
      "        -9.70017552e-01,  4.04518396e-01, -2.65233248e-01,\n",
      "        -1.65461886e+00, -1.32893384e-01, -2.54514307e-01,\n",
      "         2.72439957e-01,  1.27500200e+00,  7.48256922e-01,\n",
      "        -4.82017577e-01,  1.58087015e-01, -1.81363970e-01,\n",
      "        -1.65102527e-01,  5.82557172e-03, -1.44107640e+00,\n",
      "        -1.23197830e+00,  4.72753262e-03, -1.25886843e-01,\n",
      "        -6.73913002e-01,  8.12413812e-01, -6.98644996e-01,\n",
      "         6.78923607e-01,  3.67498785e-01, -3.66200566e-01,\n",
      "        -8.38723421e-01,  1.60439953e-01, -1.51637053e+00,\n",
      "        -1.08422793e-01,  1.99394196e-01,  1.00132883e+00,\n",
      "        -6.69311702e-01, -2.42920760e-02,  2.39341915e-01,\n",
      "        -1.01744235e+00,  7.38008559e-01, -1.33325934e+00,\n",
      "         7.31472611e-01,  2.75772065e-02,  4.32073951e-01,\n",
      "        -7.74409711e-01, -6.45154834e-01, -5.10253245e-03,\n",
      "         4.48701382e-01,  9.17340666e-02,  6.09747112e-01,\n",
      "        -5.70226729e-01, -1.03821486e-01,  1.03249228e+00,\n",
      "         3.99080485e-01, -1.41080189e+00,  5.15890956e-01,\n",
      "        -1.13435745e+00,  8.67734075e-01,  1.22731578e+00,\n",
      "        -2.76422799e-01, -1.28248811e+00,  4.61250395e-01,\n",
      "        -1.07192612e+00, -8.58278990e-01,  3.25093538e-01,\n",
      "         1.99969366e-01,  4.15551066e-01, -6.34540439e-01,\n",
      "        -6.52318239e-01,  6.05459571e-01,  4.31446493e-01,\n",
      "         3.58923614e-01,  1.76598239e+00, -8.63873780e-01,\n",
      "         4.14923608e-01,  1.24274063e+00,  1.37799427e-01,\n",
      "         4.90583748e-01,  2.21041262e-01, -1.41154826e-01,\n",
      "         9.56556350e-02,  6.61354959e-01,  3.80413800e-01,\n",
      "        -5.85337818e-01, -2.30462015e-01,  5.02348423e-01,\n",
      "        -2.90749580e-01, -4.92736518e-01, -8.59324753e-01,\n",
      "         1.25720993e-01,  2.81956285e-01, -3.22540432e-01,\n",
      "        -1.08823979e+00,  1.59655631e-01, -8.02801907e-01,\n",
      "         4.71185058e-01, -4.39298600e-01, -5.48631966e-01,\n",
      "         4.67890918e-01, -3.76239777e-01,  1.58600855e+00,\n",
      "        -2.73756117e-01, -8.46566558e-01, -1.38174430e-01,\n",
      "         1.05931580e+00,  2.98322290e-01,  1.07368052e-01,\n",
      "        -4.55769211e-01,  2.56021649e-01,  3.15838635e-01,\n",
      "        -7.36292064e-01,  2.52256930e-01, -9.44814980e-01,\n",
      "        -9.47234482e-02, -3.70331287e-01,  1.07531571e+00,\n",
      "        -1.83037177e-01, -1.67194039e-01, -8.88448954e-01,\n",
      "        -1.60342932e+00, -1.00400448e+00, -3.27926069e-01,\n",
      "        -1.10340321e+00,  2.92504076e-02, -2.90645003e-01,\n",
      "         4.07185048e-01, -4.30880308e-01, -3.62017572e-01,\n",
      "         6.13407254e-01, -6.34031892e-02, -1.19082797e+00,\n",
      "        -8.17808390e-01,  5.92283070e-01, -8.39664638e-01,\n",
      "        -8.41285527e-01, -3.42096001e-01,  1.06004775e+00,\n",
      "        -1.34889340e+00, -3.78488153e-01, -1.04030639e-01,\n",
      "         4.30296153e-01,  9.00988996e-01, -9.22017574e-01,\n",
      "        -5.80698512e-02,  1.01962948e+00, -9.49050248e-01,\n",
      "        -8.62148285e-01, -2.04318225e-01, -3.67141753e-01,\n",
      "        -1.17242277e+00, -5.61703861e-01, -6.66540444e-01,\n",
      "        -8.12579632e-01,  1.28962830e-01,  1.35237336e-01,\n",
      "        -4.78737727e-02,  1.08206081e+00, -3.08280233e-02,\n",
      "        -1.25102535e-01,  5.30636013e-01,  8.08805943e-01,\n",
      "        -1.10925937e+00,  1.52962834e-01, -6.40919507e-01,\n",
      "         1.68805957e-01,  3.60387653e-01,  1.18700206e+00,\n",
      "         2.66270012e-01, -1.72370508e-01,  8.82845163e-01,\n",
      "        -8.68109047e-01, -1.72363853e+00, -1.65520832e-01,\n",
      "         2.53288392e-02, -2.74906456e-01, -1.38105023e+00,\n",
      "        -3.49416256e-01, -9.79847610e-01, -4.41756129e-01,\n",
      "         3.61523703e-02, -8.98017585e-01, -2.95141757e-01,\n",
      "        -2.67324746e-01, -2.22984880e-01, -3.09416264e-01,\n",
      "         1.64256536e-03,  6.36047781e-01,  9.81930137e-01,\n",
      "         2.26583749e-01, -1.67089462e-01, -4.07298625e-01,\n",
      "         4.91106629e-01,  9.24779832e-01, -8.19652751e-02,\n",
      "         1.18773413e+00, -3.49886835e-01,  8.85302722e-01,\n",
      "         7.89877832e-01, -1.39533907e-01,  1.04389095e+00,\n",
      "         5.37381113e-01,  3.63890946e-01, -1.99194029e-01,\n",
      "         4.36256945e-01, -2.70932585e-01,  6.46453023e-01,\n",
      "         1.13063598e+00,  2.01903999e-01,  2.49590278e-01,\n",
      "         1.60962820e-01,  9.71734047e-01,  4.05564129e-01,\n",
      "        -2.78723449e-01,  1.07217848e+00,  4.35786366e-01,\n",
      "        -4.40292060e-01,  2.71028191e-01, -1.03908944e+00,\n",
      "        -1.06936395e+00,  3.28021646e-01,  1.43348575e+00,\n",
      "        -6.04579628e-01,  4.34845179e-01, -4.55246329e-01,\n",
      "         8.21616411e-01,  2.11315369e-03,  7.51080453e-01,\n",
      "        -5.85337818e-01,  9.38778594e-02, -6.18958771e-01,\n",
      "        -1.31025324e-02, -6.58488154e-01,  4.47551072e-01,\n",
      "        -5.24750799e-02,  5.27969360e-01, -1.11391294e+00,\n",
      "        -1.35731213e-02,  6.08805954e-01, -9.57782269e-01,\n",
      "         1.72675252e-01, -1.28756011e+00,  3.20178509e-01,\n",
      "        -8.37102532e-01,  6.00230813e-01,  5.74975908e-01,\n",
      "        -1.54488146e-01, -7.02043712e-01,  3.66296172e-01,\n",
      "         6.88596785e-01, -1.02214825e+00,  1.61956295e-01,\n",
      "        -4.84736532e-01, -4.61834550e-01,  9.06883180e-02,\n",
      "         8.05968121e-02],\n",
      "       [ 6.72371462e-02,  9.24429059e-01, -3.48506391e-01,\n",
      "        -1.54488921e-01, -3.67742091e-01, -6.22100174e-01,\n",
      "         2.85585493e-01,  1.61462510e+00, -6.23817682e-01,\n",
      "        -6.48892820e-01, -1.27554226e+00, -5.88255413e-02,\n",
      "         3.27320158e-01,  1.38585746e+00, -1.79141462e+00,\n",
      "        -5.41836858e-01, -4.32147413e-01, -1.65533340e+00,\n",
      "        -7.78733969e-01,  1.88319162e-01, -1.66266119e+00,\n",
      "         1.50585175e+00,  7.78157413e-01, -3.81424665e-01,\n",
      "        -8.67985427e-01,  7.31098592e-01, -1.45833898e+00,\n",
      "        -1.31750596e+00,  1.13573575e+00,  7.97851145e-01,\n",
      "        -6.27882361e-01,  3.07569206e-01, -8.90827835e-01,\n",
      "        -2.58854181e-01, -5.52943170e-01,  2.74708152e-01,\n",
      "         1.49829483e+00,  3.39456975e-01, -1.94334343e-01,\n",
      "         9.83806998e-02, -2.73738950e-01, -1.28441596e+00,\n",
      "         3.13122362e-01,  2.88218975e-01,  5.14982939e-01,\n",
      "         5.53568900e-01, -5.91700912e-01, -9.26025584e-02,\n",
      "         4.36322600e-01, -8.71363103e-01, -2.63548613e-01,\n",
      "        -1.85221210e-02, -1.05513299e+00,  1.53121417e-02,\n",
      "        -5.34222722e-01, -2.32165530e-02,  1.54180419e+00,\n",
      "        -1.16430712e+00,  6.20722175e-01,  2.13165298e-01,\n",
      "         1.48856246e+00, -9.60099339e-01, -4.40391302e-01,\n",
      "        -4.93518531e-01, -8.68042648e-01, -1.62217557e-01,\n",
      "         1.47224641e+00, -8.23044777e-01,  3.81420642e-01,\n",
      "         2.61712611e-01,  3.06195199e-01, -8.40162337e-01,\n",
      "        -5.53572953e-01,  4.26819235e-01,  1.26964164e+00,\n",
      "        -8.09419513e-01,  1.41894746e+00, -5.26837587e-01,\n",
      "         5.97536266e-01,  2.66235292e-01,  7.39685953e-01,\n",
      "        -1.03755748e+00,  9.38512385e-01,  1.09966886e+00,\n",
      "         4.03872803e-02, -1.56545210e+00,  1.29295260e-01,\n",
      "        -1.56492636e-01, -7.99057424e-01,  6.14596546e-01,\n",
      "        -2.97840863e-01,  6.50777996e-01,  7.35450676e-03,\n",
      "        -3.19366544e-01, -6.33206546e-01,  2.95661360e-01,\n",
      "         5.27463257e-01, -8.72508109e-01,  2.72818953e-01,\n",
      "        -1.12199998e+00, -8.22071552e-01,  8.27048242e-01,\n",
      "         5.75620346e-02,  9.21405405e-02,  1.83567479e-01,\n",
      "        -4.94091034e-01,  1.97708026e-01,  9.39829111e-01,\n",
      "        -1.25126863e+00,  1.01436758e+00,  6.58735633e-01,\n",
      "         2.86787748e-01,  8.78858745e-01, -6.34627268e-02,\n",
      "        -9.68389958e-02,  2.48659790e-01, -2.30973825e-01,\n",
      "        -8.00431371e-01,  1.30404842e+00,  5.68625450e-01,\n",
      "        -5.36798894e-01, -1.85403466e-01,  1.32883728e+00,\n",
      "         1.31127223e-01, -1.35997429e-01, -1.42444742e+00,\n",
      "         7.04706728e-01, -2.43510259e-03,  2.32801765e-01,\n",
      "         4.63802189e-01, -6.26050413e-01, -1.54593015e+00,\n",
      "        -7.76443958e-01,  9.21394885e-01, -4.14514691e-01,\n",
      "         1.41260326e-01,  4.43879485e-01,  2.40186915e-01,\n",
      "        -1.42638341e-01,  9.99836773e-02,  6.89134955e-01,\n",
      "         1.24559700e+00,  6.87131226e-01, -6.20887466e-02,\n",
      "         9.07311559e-01,  2.10531831e-01,  3.69169295e-01,\n",
      "        -2.93547153e-01,  1.88615918e-02, -9.73152161e-01,\n",
      "         2.90337175e-01,  3.90408754e-01, -2.64808089e-01,\n",
      "        -1.34263837e+00,  6.14940047e-01, -5.85002720e-01,\n",
      "         7.93671966e-01,  7.67967045e-01, -1.03463781e+00,\n",
      "        -6.94749415e-01, -5.42924583e-01,  4.23337519e-02,\n",
      "        -1.46658278e+00,  1.10699666e+00, -8.32136944e-02,\n",
      "         1.13619491e-02,  1.33593619e+00,  1.64611220e+00,\n",
      "         4.06438529e-01,  3.51479322e-01, -2.95665383e-01,\n",
      "        -1.99257776e-01,  1.29242682e+00,  7.35564053e-01,\n",
      "         8.77198517e-01, -6.07902408e-01,  2.81406313e-01,\n",
      "        -5.88208675e-01, -1.20970571e+00,  6.02974951e-01,\n",
      "         5.10517538e-01,  6.85528278e-01, -1.07906318e+00,\n",
      "         4.72389579e-01,  1.28338146e+00, -8.97869468e-01,\n",
      "         8.01572323e-01, -6.58682406e-01, -5.59698582e-01,\n",
      "        -1.01792097e+00, -2.86219269e-01,  6.85929000e-01,\n",
      "         7.64131367e-01, -6.72422230e-01, -2.51927018e-01,\n",
      "        -1.30702937e+00, -6.72822952e-01,  5.46641767e-01,\n",
      "        -7.28240192e-01, -7.98542142e-01,  2.67552018e-01,\n",
      "         1.19012249e+00, -3.49823117e-01,  1.37435031e+00,\n",
      "        -4.14342940e-01,  1.91238865e-01,  1.28647292e+00,\n",
      "         1.38963592e+00,  2.19348207e-01, -1.68395793e+00,\n",
      "        -7.66368151e-01,  7.35964775e-01, -1.30273569e+00,\n",
      "         1.66965216e-01, -1.05082877e-01,  1.67022467e-01,\n",
      "         5.45897543e-01, -1.17792197e-01, -1.06972098e-01,\n",
      "        -7.47075140e-01,  8.44118968e-02, -3.64421636e-01,\n",
      "         2.80547589e-01,  7.04363227e-01, -5.43210804e-01,\n",
      "        -8.85961652e-01, -1.53860223e+00, -6.09390855e-01,\n",
      "         9.80372056e-02, -3.91443253e-01,  1.08026135e+00,\n",
      "         2.45110333e-01,  1.70800909e-01,  5.68968952e-01,\n",
      "         8.15999150e-01, -1.45988464e+00, -6.60857916e-01,\n",
      "         1.21685791e+00, -2.93661654e-01,  1.83109477e-01,\n",
      "        -6.73567176e-01,  5.26203811e-01,  3.94702435e-01,\n",
      "         7.92469740e-01, -5.48592269e-01, -4.51096892e-01,\n",
      "        -1.26592445e+00, -1.13040514e-01, -1.09411967e+00,\n",
      "         8.75033513e-02, -1.27066568e-01, -4.98946719e-02,\n",
      "        -4.02835846e-01,  7.81144872e-02,  3.53493541e-02,\n",
      "        -1.34566203e-01,  1.34171832e+00,  8.28661695e-02,\n",
      "        -5.05827129e-01,  5.60725033e-01, -5.12639761e-01,\n",
      "        -9.41779613e-01, -6.44770861e-01,  1.15898944e-01,\n",
      "        -2.51469016e-01,  6.98981822e-01,  1.54684210e+00,\n",
      "        -3.06599975e-01,  2.03089446e-01,  3.89721751e-01,\n",
      "         3.26003432e-01, -6.31603539e-01,  2.19348207e-01,\n",
      "        -1.47482669e+00,  9.33531702e-01,  9.49904978e-01,\n",
      "        -9.06560868e-02, -1.20856071e+00,  1.20924377e+00,\n",
      "        -3.37504037e-02, -1.71377420e-01,  7.80962646e-01,\n",
      "        -9.07133371e-02, -3.48048389e-01,  5.47214270e-01,\n",
      "        -1.24542928e+00,  5.66736221e-01,  7.58817717e-02,\n",
      "         6.23985410e-01, -1.52446175e+00,  3.87832522e-01,\n",
      "         7.74847493e-02,  5.94616592e-01, -5.49336493e-01,\n",
      "        -1.94677845e-01, -1.09280288e+00, -8.92717063e-01,\n",
      "        -5.58152854e-01, -3.15176845e-02,  8.77323523e-02,\n",
      "         4.66274433e-02, -8.07988286e-01, -1.33993715e-01,\n",
      "        -2.03494206e-01,  1.71029910e-01, -1.29403377e+00,\n",
      "        -5.44069588e-01,  1.43211472e+00, -8.31231415e-01,\n",
      "         1.56670761e+00, -4.47547466e-01,  3.90981227e-01,\n",
      "         6.42029420e-02,  2.49461278e-01, -1.04935086e+00,\n",
      "         6.30111039e-01,  1.93757832e-01, -7.63333917e-01,\n",
      "        -7.71978557e-01,  1.01018834e+00,  5.60610533e-01,\n",
      "        -3.98370415e-01,  1.06188440e+00, -5.46302259e-01,\n",
      "         4.28021461e-01, -1.47905260e-01, -9.56435382e-01,\n",
      "         2.34404743e-01, -1.37057590e+00, -5.50767720e-01,\n",
      "         7.62986422e-01, -1.03360724e+00,  1.64216197e+00,\n",
      "         4.85556871e-01,  9.69369650e-01, -1.27943528e+00,\n",
      "        -7.67169595e-01, -1.63763285e-01,  2.02001706e-01,\n",
      "        -1.20592725e+00,  9.72346663e-01, -4.02768105e-02,\n",
      "         1.25767648e+00,  1.64675251e-01, -1.60054588e+00,\n",
      "         2.04635173e-01,  2.60109633e-01, -7.68028319e-01,\n",
      "        -1.91242889e-01,  6.27305865e-01,  9.73548889e-01,\n",
      "        -2.09906116e-01, -3.31331611e-01,  4.17612605e-02,\n",
      "         6.11963093e-01,  6.86444223e-01,  8.28765690e-01,\n",
      "         8.99650678e-02, -2.60628879e-01,  4.63973939e-01,\n",
      "         1.61760211e+00,  2.43049368e-01,  4.66379523e-03,\n",
      "         7.07683682e-01,  5.62728763e-01,  1.06211329e+00,\n",
      "        -1.02250099e+00,  8.08213234e-01, -1.16876207e-01,\n",
      "        -1.60329390e+00,  6.56352844e-04,  1.45449924e+00,\n",
      "         6.93657637e-01, -2.64693588e-01, -2.35611007e-01,\n",
      "         5.48187494e-01, -5.97712040e-01, -2.20153719e-01,\n",
      "        -1.22773921e+00,  3.79760414e-01,  1.11621380e+00,\n",
      "        -7.72894502e-01,  7.30640590e-01, -1.17505945e-01,\n",
      "        -1.17398226e+00, -1.12806845e+00, -6.14142537e-01,\n",
      "        -8.84530425e-01, -6.11165583e-01,  1.70514658e-01,\n",
      "         7.79130638e-01, -5.32963216e-01, -4.06957775e-01,\n",
      "        -6.39561176e-01,  8.28364968e-01,  9.37939882e-01,\n",
      "         8.68553877e-01,  1.40401587e-01,  1.21738359e-01,\n",
      "        -5.36398172e-01,  9.22883332e-01, -1.12011075e+00,\n",
      "        -5.98399043e-01,  8.81377697e-01,  2.59995133e-01,\n",
      "        -7.47933865e-01, -1.98341787e-01,  1.72289386e-01,\n",
      "         1.28780007e-01, -5.38802624e-01,  6.65491045e-01,\n",
      "        -6.16776049e-01,  3.66478592e-01,  7.27377415e-01,\n",
      "         7.06023455e-01, -1.72236159e-01, -7.64192641e-01,\n",
      "         7.40029454e-01,  9.05880332e-01,  2.31198788e-01,\n",
      "        -3.03222269e-01, -5.99132776e-02, -9.02563930e-01,\n",
      "         1.13968599e+00, -1.56900156e+00, -3.68200094e-01,\n",
      "        -2.52842993e-01, -9.13155019e-01,  1.07322084e-02,\n",
      "         9.07665566e-02, -1.54431671e-01, -1.73771381e-02,\n",
      "         1.16098273e+00, -6.55648232e-01, -9.09662783e-01,\n",
      "         3.24457705e-01,  8.02373827e-01, -4.32662666e-01,\n",
      "         5.75724363e-01,  4.38794829e-02,  5.24085581e-01,\n",
      "        -8.34780872e-01, -1.02427566e+00,  1.10190153e+00,\n",
      "        -1.09039843e+00,  8.97235692e-01,  4.35932353e-02,\n",
      "        -7.44384408e-01, -1.80766284e-01,  3.13866615e-01,\n",
      "        -5.88094175e-01,  4.52123374e-01,  7.99282372e-01,\n",
      "         7.76382685e-01,  2.17859730e-01, -1.29127532e-01,\n",
      "        -2.65781313e-01,  8.56141299e-02, -4.04267073e-01,\n",
      "        -1.19108923e-01,  6.94802642e-01,  9.52319950e-02,\n",
      "        -4.24590528e-01,  8.51665378e-01, -3.90012026e-01,\n",
      "        -1.88895673e-01,  5.62728763e-01, -8.29800189e-01,\n",
      "        -2.78719634e-01, -4.49722916e-01,  1.11197734e+00,\n",
      "         4.29738939e-01,  5.04735351e-01, -4.76973534e-01,\n",
      "         5.64789772e-01,  6.73219681e-01,  8.69240880e-01,\n",
      "        -4.09705758e-01, -2.56621450e-01, -6.33092046e-01,\n",
      "        -2.06184924e-01,  7.84579813e-02,  6.40244186e-01,\n",
      "        -4.52528119e-01, -6.90158978e-02,  2.95260608e-01,\n",
      "        -4.74168330e-01,  1.31343722e+00,  7.13523090e-01,\n",
      "        -1.11238217e+00,  8.60195518e-01, -8.13083470e-01,\n",
      "        -5.03422678e-01, -1.23254812e+00,  6.93256915e-01,\n",
      "         2.96119362e-01,  5.15956223e-01,  1.37314808e+00,\n",
      "         5.99665008e-02, -8.42441767e-02,  1.25069330e-02,\n",
      "        -4.95007008e-01,  1.51088965e+00, -8.94720793e-01,\n",
      "        -6.33836269e-01, -2.03150719e-01,  1.00606644e+00,\n",
      "        -6.30619824e-02, -6.72411695e-02, -5.12582541e-01,\n",
      "         1.36347306e+00, -6.12883091e-01,  4.57733780e-01,\n",
      "        -3.94076735e-01, -5.18650949e-01, -4.33693141e-01,\n",
      "        -1.19280674e-01, -2.84387290e-01,  2.85070270e-01,\n",
      "        -8.82984698e-01, -1.01814997e+00,  7.96190917e-01,\n",
      "         4.34834123e-01, -1.16121566e+00,  9.32282731e-02,\n",
      "        -3.12611133e-01, -1.21617496e+00, -8.31116915e-01,\n",
      "         2.19530463e-02, -1.32512009e+00, -2.82498091e-01,\n",
      "         1.02661884e+00,  3.13580364e-01, -3.79592687e-01,\n",
      "        -8.66486430e-02, -1.02021098e+00, -3.46788913e-01,\n",
      "         3.41117203e-01, -2.19294980e-01,  5.95189035e-01,\n",
      "        -7.82226145e-01, -5.61072588e-01,  6.31599545e-01,\n",
      "        -1.13012934e+00,  1.26803863e+00, -3.75184506e-01,\n",
      "        -3.57437253e-01,  1.06440330e+00,  7.54227281e-01,\n",
      "         4.24357504e-01,  2.55529702e-01, -3.74268502e-01,\n",
      "        -2.14990787e-02,  2.28107333e-01, -9.49622750e-01,\n",
      "        -6.42423630e-01,  5.80132544e-01,  2.37725198e-01,\n",
      "         2.94516385e-01,  7.16385543e-01,  4.33517367e-01,\n",
      "        -1.66054296e+00, -3.80565912e-01, -6.07501626e-01,\n",
      "        -1.09142900e+00, -5.49622715e-01, -6.69387996e-01,\n",
      "        -4.06270802e-01,  7.27262914e-01,  6.67952776e-01,\n",
      "         1.76926568e-01,  1.06921220e+00,  3.57318729e-01,\n",
      "         2.13508800e-01,  9.20307159e-01,  4.72618580e-01,\n",
      "        -5.05025625e-01, -9.41894114e-01, -4.43368256e-01,\n",
      "         8.29624414e-01, -8.89374933e-04,  1.75551534e+00,\n",
      "        -1.02334917e-01,  3.45983386e-01, -9.30558741e-01,\n",
      "         1.06073940e+00, -9.35940206e-01,  6.38870180e-01,\n",
      "        -5.26207805e-01, -4.72794354e-01, -4.33521420e-01,\n",
      "         5.73902875e-02,  1.22527349e+00,  1.16338718e+00,\n",
      "        -3.77302706e-01, -6.18321776e-01,  4.18403596e-01,\n",
      "         8.90594780e-01,  6.46541595e-01,  9.30611968e-01,\n",
      "         1.99768990e-01,  5.45496762e-01, -1.04624882e-01,\n",
      "         1.04391858e-01,  1.50305703e-01, -7.19939053e-01,\n",
      "         1.47156999e-01, -3.44441682e-01,  4.44680959e-01,\n",
      "         5.22253633e-01,  6.14825547e-01,  1.84769705e-01,\n",
      "        -6.87593281e-01,  4.03300337e-02, -2.30448060e-02,\n",
      "         5.29820994e-02,  3.09515655e-01, -4.67126667e-01,\n",
      "        -6.28329813e-02,  1.41900468e+00,  5.01243174e-01,\n",
      "        -3.31779122e-02, -6.61429251e-03, -6.79281577e-02,\n",
      "         4.76568758e-01,  1.04436612e+00, -5.06056130e-01,\n",
      "        -3.22400749e-01, -5.30959487e-01, -7.02649772e-01,\n",
      "         7.17988551e-01, -4.40563053e-01,  4.14796889e-01,\n",
      "         5.90723634e-01,  1.16287184e+00,  1.07482266e+00,\n",
      "        -7.32762873e-01, -4.77946758e-01, -1.14049149e+00,\n",
      "        -4.03580099e-01,  5.77670813e-01,  1.11434632e-03,\n",
      "        -3.94534707e-01,  2.95203358e-01, -7.21828282e-01,\n",
      "        -6.31260037e-01,  1.86945170e-01,  9.36966658e-01,\n",
      "         8.25960517e-01, -5.29288761e-02, -3.03794771e-01,\n",
      "         3.49361092e-01, -4.38673824e-01, -6.46316588e-01,\n",
      "         2.19004720e-01, -1.20826401e-01, -7.37571776e-01,\n",
      "         1.00807011e+00, -1.14094949e+00,  8.44118968e-02,\n",
      "        -4.55562353e-01,  1.48931727e-01,  1.29700673e+00,\n",
      "         3.65276366e-01,  2.01085716e-01,  1.24113154e+00,\n",
      "         7.67967045e-01, -7.65394866e-01, -9.30329740e-01,\n",
      "        -9.55175936e-01,  7.58635461e-01,  1.63237238e+00,\n",
      "         1.48426878e+00, -4.41822529e-01,  9.34447706e-01,\n",
      "        -5.87006450e-01,  4.31456417e-01, -5.08575082e-01,\n",
      "         1.43549252e+00,  4.13365662e-01,  8.17211866e-02,\n",
      "         9.29992720e-02, -4.74855304e-01, -2.30630323e-01,\n",
      "        -6.47862315e-01, -1.22257628e-01, -2.64407337e-01,\n",
      "        -8.16107169e-02, -1.65773785e+00, -5.54431677e-01,\n",
      "        -9.66625750e-01,  1.15050602e+00,  1.32568860e+00,\n",
      "         3.74894232e-01, -7.11237192e-01,  3.35335046e-01,\n",
      "        -6.87879503e-01,  5.92795089e-02,  4.28937435e-01,\n",
      "         2.07669377e-01,  1.15365481e+00,  3.93442959e-01,\n",
      "        -2.14085311e-01, -5.93819082e-01,  8.89736056e-01,\n",
      "        -1.42523840e-01,  1.35242391e+00, -5.79106092e-01,\n",
      "        -2.87421495e-01,  3.61039937e-01, -1.24640250e+00,\n",
      "        -7.69974828e-01,  1.15485704e+00,  2.82665789e-01,\n",
      "         7.56231010e-01,  1.50585175e+00,  1.28103423e+00,\n",
      "        -3.50796342e-01,  2.51522243e-01, -1.34910750e+00,\n",
      "        -1.13774347e+00,  7.07855463e-01,  4.40845281e-01,\n",
      "         1.50076702e-01,  1.52583170e+00,  1.12199593e+00,\n",
      "         8.04892778e-01,  2.63372838e-01,  6.14253044e-01,\n",
      "        -7.70432830e-01, -7.21942782e-01, -8.91629338e-01,\n",
      "        -8.24132562e-01,  3.17530543e-01,  9.20020878e-01,\n",
      "        -6.19695723e-01, -9.32276249e-01,  1.04322112e+00,\n",
      "        -2.55247474e-01,  1.15703249e+00, -1.78991571e-01,\n",
      "         8.99239421e-01,  1.15165102e+00, -2.36641482e-01,\n",
      "        -3.92473757e-01, -4.45142984e-01,  9.31814194e-01,\n",
      "         2.65033066e-01,  2.73792177e-01, -3.34251344e-01,\n",
      "         2.79402584e-01, -4.17892367e-01, -1.71321225e+00,\n",
      "        -6.36298001e-01,  4.70328599e-01, -1.01476178e-01,\n",
      "         3.66421342e-01, -1.21960986e+00,  4.50520396e-01,\n",
      "        -7.49307871e-01, -8.16679671e-02, -6.39160454e-01,\n",
      "         5.46412766e-01,  8.41933012e-01,  8.41990232e-01,\n",
      "        -3.22046764e-02, -4.11022484e-01, -5.98055542e-01,\n",
      "         1.08879149e+00, -4.00145143e-01,  1.10699666e+00,\n",
      "        -1.73839137e-01, -8.80122244e-01, -1.77445844e-01,\n",
      "        -7.48334646e-01,  3.82909119e-01, -1.00166225e+00,\n",
      "        -1.01740575e+00,  5.74235857e-01,  3.60753685e-01,\n",
      "        -6.49637043e-01,  7.16786325e-01,  1.06680775e+00,\n",
      "         2.99611568e-01,  1.43846941e+00, -4.06786054e-01,\n",
      "        -4.28540736e-01, -5.01705170e-01, -8.07473004e-01,\n",
      "         6.31714046e-01,  3.80790889e-01,  9.18542892e-02,\n",
      "         1.12039304e+00, -3.08260202e-01,  2.36465707e-01,\n",
      "         1.98108763e-01, -4.79482003e-02,  1.01167679e+00,\n",
      "         1.17289054e+00, -1.64335772e-01,  3.45296413e-01,\n",
      "        -2.53472745e-01,  2.54899949e-01,  1.70800909e-01,\n",
      "         9.67204720e-02, -3.43697459e-01, -4.18808371e-01,\n",
      "         7.91449770e-02,  5.45611262e-01,  1.61342287e+00,\n",
      "         1.20192632e-01, -4.21899825e-01, -6.09848857e-01,\n",
      "        -8.54016602e-01,  4.74107057e-01,  3.00756544e-01,\n",
      "         4.42229770e-02,  1.56374112e-01,  2.73677677e-01,\n",
      "        -3.81023914e-01, -6.90054953e-01, -1.23345368e-01,\n",
      "         9.14410472e-01,  7.21137226e-01, -7.35110044e-01,\n",
      "         4.89746593e-02,  4.48527187e-02, -8.05297554e-01,\n",
      "        -1.46532333e+00, -6.11909866e-01,  7.85724819e-02,\n",
      "        -9.43153560e-01, -8.76801789e-01,  6.33030772e-01,\n",
      "         3.70095819e-02, -5.40520132e-01,  8.52133855e-02,\n",
      "         9.16252956e-02,  4.99411196e-01,  1.37852955e+00,\n",
      "        -2.88337499e-01, -6.54664487e-02,  2.76207160e-02,\n",
      "        -9.47733521e-01, -6.46373868e-01, -1.96738809e-01,\n",
      "        -1.60843581e-01, -1.37657657e-01, -1.14242747e-01,\n",
      "        -2.40419924e-01,  8.50416422e-02,  5.56889355e-01,\n",
      "         3.59150708e-01, -3.59269232e-01,  1.17088675e+00,\n",
      "         1.42233565e-01,  6.94001138e-01,  2.89077699e-01,\n",
      "         1.28493771e-01,  8.61970246e-01,  5.69541454e-01,\n",
      "         1.08467061e-02, -5.69488227e-01,  5.49847722e-01,\n",
      "        -9.30272520e-01, -5.24146855e-01, -4.05412048e-01,\n",
      "        -8.14571917e-01,  9.04792607e-01,  3.83080870e-01,\n",
      "         4.97121215e-01,  7.13294089e-01, -9.36569929e-01,\n",
      "        -1.67427227e-01,  1.31074655e+00, -8.11881244e-01,\n",
      "         1.89521387e-01, -1.76129103e-01, -6.50896549e-01,\n",
      "         3.88863027e-01,  1.25173315e-01,  4.52180624e-01,\n",
      "        -1.13539636e+00, -3.76787484e-01, -8.90427113e-01,\n",
      "         4.43374738e-02, -6.15974545e-01,  2.05207661e-01,\n",
      "         2.64059812e-01, -3.91214252e-01, -2.27882355e-01,\n",
      "        -2.65895814e-01,  6.12020314e-01, -2.44427368e-01,\n",
      "        -1.49050251e-01, -8.93518567e-01,  1.10287476e+00,\n",
      "        -5.68686724e-01,  2.05207661e-01,  2.68353492e-01,\n",
      "         7.42376685e-01, -1.84716478e-01, -6.18894219e-01,\n",
      "        -6.91657960e-01, -2.33836278e-01,  1.09143540e-01,\n",
      "         7.50048101e-01,  5.90551853e-01, -1.03594400e-01,\n",
      "        -5.30433767e-02, -5.12926042e-01,  1.00452183e-02,\n",
      "         5.49046218e-01,  5.04907131e-01, -1.68510294e+00,\n",
      "         4.39070553e-01,  1.05810595e+00, -6.26393855e-01,\n",
      "        -5.80880761e-01,  7.51375332e-02, -1.34108216e-01,\n",
      "        -1.96796060e-01,  5.45096040e-01, -2.90913701e-01,\n",
      "         3.78042936e-01,  3.06882203e-01,  5.71612902e-02,\n",
      "         7.10546136e-01, -4.57727313e-02, -6.38530731e-01,\n",
      "        -7.00417042e-01, -5.70003450e-01,  6.38297677e-01,\n",
      "        -6.16089046e-01, -8.20114613e-02, -2.26794630e-01,\n",
      "        -4.62145984e-01,  1.59201169e+00, -1.76930591e-01,\n",
      "        -6.30047321e-02,  3.12549859e-01, -6.60915136e-01,\n",
      "        -9.53458428e-01, -3.06313723e-01, -5.65928258e-02,\n",
      "        -3.79191935e-01,  8.78171742e-01, -2.15001300e-01,\n",
      "         2.25255378e-02, -1.77744579e+00, -6.92516685e-01,\n",
      "        -3.45071435e-01, -3.84573370e-01, -7.81081140e-01,\n",
      "         1.95818797e-01,  1.77738573e-02,  1.05896461e+00,\n",
      "        -4.96667236e-01,  1.49039447e+00, -8.67641926e-01,\n",
      "        -1.27124858e+00,  8.40845287e-01,  5.03819346e-01,\n",
      "        -1.25207019e+00, -3.33392590e-01, -3.80909413e-01,\n",
      "        -2.22157449e-01,  1.77613556e-01, -2.10879356e-01,\n",
      "        -6.57022178e-01,  1.16418862e+00,  5.68739951e-01,\n",
      "        -9.38459158e-01,  6.12363815e-01, -6.95837140e-01,\n",
      "         3.54066044e-02, -4.28998709e-01, -2.39904687e-01,\n",
      "         4.71359074e-01, -3.10664684e-01, -1.06893003e+00,\n",
      "         1.29053760e+00,  7.96648920e-01,  9.99654472e-01,\n",
      "         3.35449547e-01, -5.92502356e-01, -3.24909203e-02,\n",
      "         1.12073648e+00,  1.01293635e+00, -2.64750838e-01,\n",
      "         2.28336334e-01, -8.72508109e-01, -1.12749588e+00,\n",
      "        -3.69688570e-01,  5.08571029e-01,  1.35592669e-01,\n",
      "         6.41217411e-01, -2.09219128e-01, -2.61602134e-01,\n",
      "        -4.15257784e-03,  3.99110615e-01, -4.39532578e-01,\n",
      "         8.73649061e-01, -4.98499215e-01, -2.78376132e-01,\n",
      "         7.52910554e-01,  6.68181777e-01,  1.77212819e-01,\n",
      "        -2.32118800e-01,  7.76897967e-01, -3.24805230e-01,\n",
      "         1.08685553e-01, -3.35568070e-01,  9.90895391e-01,\n",
      "         1.62099034e-01, -8.53100598e-01, -2.54159749e-01,\n",
      "        -5.92903137e-01, -4.60600257e-01,  1.86258182e-01,\n",
      "         9.09086287e-01, -3.79295908e-02, -9.23574388e-01,\n",
      "        -9.88666654e-01]], dtype=float32)}\n",
      "try_input_function: labels = [[0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]\n",
      " [1. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]\n",
      " [0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]\n",
      " [0. 0. 0. 1. 0. 1. 0. 1. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 1. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]\n",
      " [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n",
      "  0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "try_input_function()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Create our model function to be used in our custom estimator\n",
    "def video_level_model(features, labels, mode, params):\n",
    "  print(\"\\nvideo_level_model: features = {}\".format(features))\n",
    "  print(\"video_level_model: labels = {}\".format(labels))\n",
    "  print(\"video_level_model: mode = {}\".format(mode))\n",
    "\n",
    "  # 0. Configure network\n",
    "  # Get dynamic batch size\n",
    "  current_batch_size = tf.shape(features['mean_rgb'])[0]\n",
    "  print(\"video_level_model: current_batch_size = {}\".format(current_batch_size))\n",
    "\n",
    "  # Stack all of the features into a 3-D tensor\n",
    "  combined_features = tf.concat(values = [features['mean_rgb'], features['mean_audio']], axis = 1) # shape = (current_batch_size, 1024 + 128)\n",
    "  print(\"video_level_model: combined_features = {}\".format(combined_features))\n",
    "\n",
    "  # 1. Create the DNN structure now\n",
    "  # Create the input layer to our frame DNN\n",
    "  network = combined_features # shape = (current_batch_size, 1024 + 128)\n",
    "  print(\"video_level_model: network = combined_features = {}\".format(network))\n",
    "\n",
    "  # Add hidden layers with the given number of units/neurons per layer\n",
    "  for units in params['hidden_units']:\n",
    "    network = tf.layers.dense(inputs = network, units = units, activation = tf.nn.relu) # shape = (current_batch_size, units)\n",
    "    print(\"video_level_model: network = {}, units = {}\".format(network, units))\n",
    "\n",
    "  # Connect the final hidden layer to a dense layer with no activation to get the logits\n",
    "  logits = tf.layers.dense(inputs = network, units = NUM_CLASSES, activation = None) # shape = (current_batch_size, NUM_CLASSES)\n",
    "  print(\"video_level_model: logits = {}\".format(logits))\n",
    "\n",
    "  # Select the top k logits in descending order\n",
    "  top_k_logits = tf.nn.top_k(input = logits, k = params['top_k'], sorted = True) # shape = (current_batch_size, top_k)\n",
    "  print(\"video_level_model: top_k_logits = {}\".format(top_k_logits))\n",
    "\n",
    "  # Since this is a multi-class, multi-label problem we will apply a sigmoid, not a softmax, to each logit to get its own probability\n",
    "  probabilities = tf.sigmoid(logits) # shape = (current_batch_size, NUM_CLASSES)\n",
    "  print(\"video_level_model: probabilities = {}\".format(probabilities))\n",
    "\n",
    "  # Select the top k probabilities in descending order\n",
    "  top_k_probabilities = tf.sigmoid(top_k_logits.values) # shape = (current_batch_size, top_k)\n",
    "  print(\"video_level_model: top_k_probabilities = {}\".format(top_k_probabilities))\n",
    "\n",
    "  # Select the top k classes in descending order of likelihood\n",
    "  top_k_classes = top_k_logits.indices # shape = (current_batch_size, top_k)\n",
    "  print(\"video_level_model: top_k_classes = {}\".format(top_k_classes))\n",
    "\n",
    "  # The 0/1 predictions based on a threshold, in this case the threshold is if the probability it greater than random chance\n",
    "  predictions = tf.where(\n",
    "    condition = probabilities > 1.0 / NUM_CLASSES, # shape = (current_batch_size, NUM_CLASSES)\n",
    "    x = tf.ones_like(tensor = probabilities), \n",
    "    y = tf.zeros_like(tensor = probabilities))\n",
    "  print(\"video_level_model: predictions = {}\".format(predictions))\n",
    "\n",
    "  top_k_predictions = tf.where(\n",
    "    condition = top_k_probabilities > 1.0 / NUM_CLASSES, # shape = (current_batch_size, top_k)\n",
    "    x = tf.ones_like(tensor = top_k_probabilities), \n",
    "    y = tf.zeros_like(tensor = top_k_probabilities))\n",
    "  print(\"video_level_model: top_k_predictions = {}\\n\".format(top_k_predictions))\n",
    "\n",
    "  # 2. Loss function, training/eval ops \n",
    "  if mode == tf.estimator.ModeKeys.TRAIN or mode == tf.estimator.ModeKeys.EVAL:\n",
    "    # Since this is a multi-class, multi-label problem, we will use sigmoid activation and cross entropy loss\n",
    "    loss = tf.losses.sigmoid_cross_entropy(multi_class_labels = labels, logits = logits)\n",
    "\n",
    "    train_op = tf.contrib.layers.optimize_loss(\n",
    "      loss = loss,\n",
    "      global_step = tf.train.get_global_step(),\n",
    "      learning_rate = 0.01,\n",
    "      optimizer = \"Adam\")\n",
    "    eval_metric_ops = {\n",
    "      \"accuracy\": tf.metrics.mean_per_class_accuracy(labels = labels, predictions = predictions, num_classes = NUM_CLASSES)\n",
    "    }\n",
    "  else:\n",
    "    loss = None\n",
    "    train_op = None\n",
    "    eval_metric_ops = None\n",
    "\n",
    "  # 3. Create predictions\n",
    "  predictions_dict = {\"logits\": top_k_logits.values, \n",
    "                      \"probabilities\": top_k_probabilities, \n",
    "                      \"predictions\": top_k_predictions,\n",
    "                      \"classes\": top_k_classes}\n",
    "\n",
    "  # 4. Create export outputs\n",
    "  export_outputs = {\"predict_export_outputs\": tf.estimator.export.PredictOutput(outputs = predictions_dict)}\n",
    "\n",
    "  # 5. Return EstimatorSpec\n",
    "  return tf.estimator.EstimatorSpec(\n",
    "      mode = mode,\n",
    "      predictions = predictions_dict,\n",
    "      loss = loss,\n",
    "      train_op = train_op,\n",
    "      eval_metric_ops = eval_metric_ops,\n",
    "      export_outputs = export_outputs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Create our serving input function to accept the data at serving and send it in the right format to our custom estimator\n",
    "def serving_input_fn():\n",
    "  # This function fixes the shape and type of our input strings\n",
    "  def fix_shape_and_type_for_serving(placeholder):\n",
    "    # String split each string in the batch and output the values from the resulting SparseTensors\n",
    "    split_string = tf.map_fn(\n",
    "      fn = lambda x: tf.string_split(source = [placeholder[x]], delimiter=',').values, \n",
    "      elems = tf.range(start = 0, limit = tf.shape(input = placeholder)[0]), \n",
    "      dtype = tf.string) # shape = (batch_size, input_sequence_length)\n",
    "    print(\"serving_input_fn: fix_shape_and_type_for_serving: split_string = {}\".format(split_string))\n",
    "\n",
    "    # Convert each string in the split tensor to float\n",
    "    feature_tensor = tf.string_to_number(string_tensor = split_string, out_type = tf.float32) # shape = (batch_size, input_sequence_length)\n",
    "    print(\"serving_input_fn: fix_shape_and_type_for_serving: feature_tensor = {}\".format(feature_tensor))\n",
    "    return feature_tensor\n",
    "  \n",
    "  # This function fixes dynamic shape ambiguity of last dimension so that we will be able to use it in our DNN (since tf.layers.dense require the last dimension to be known)\n",
    "  def get_shape_and_set_modified_shape_2D(tensor, additional_dimension_sizes):\n",
    "    # Get static shape for tensor and convert it to list\n",
    "    shape = tensor.get_shape().as_list()\n",
    "    # Set outer shape to additional_dimension_sizes[0] since we know that this is the correct size\n",
    "    shape[1] = additional_dimension_sizes[0]\n",
    "    # Set the shape of tensor to our modified shape\n",
    "    tensor.set_shape(shape = shape) # shape = (batch_size, additional_dimension_sizes[0])\n",
    "    print(\"serving_input_fn: get_shape_and_set_modified_shape_2D: tensor = {}, additional_dimension_sizes = {}\".format(tensor, additional_dimension_sizes))\n",
    "    return tensor\n",
    "  \n",
    "  # Create placeholders to accept the data sent to the model at serving time\n",
    "  feature_placeholders = { # all features come in as a batch of strings, shape = (batch_size,), this was so because of passing the arrays to online ml-engine prediction\n",
    "    'video_id': tf.placeholder(dtype = tf.string, shape = [None]),\n",
    "    'mean_rgb': tf.placeholder(dtype = tf.string, shape = [None]),\n",
    "    'mean_audio': tf.placeholder(dtype = tf.string, shape = [None])\n",
    "  }\n",
    "  print(\"\\nserving_input_fn: feature_placeholders = {}\".format(feature_placeholders))\n",
    "\n",
    "  # Create feature tensors\n",
    "  features = {\n",
    "    \"video_id\": feature_placeholders[\"video_id\"],\n",
    "    \"mean_rgb\": fix_shape_and_type_for_serving(placeholder = feature_placeholders[\"mean_rgb\"]),\n",
    "    \"mean_audio\": fix_shape_and_type_for_serving(placeholder = feature_placeholders[\"mean_audio\"])\n",
    "  }\n",
    "  print(\"serving_input_fn: features = {}\".format(features))\n",
    "\n",
    "  # Fix dynamic shape ambiguity of feature tensors for our DNN\n",
    "  features[\"mean_rgb\"] = get_shape_and_set_modified_shape_2D(tensor = features[\"mean_rgb\"], additional_dimension_sizes = [1024])\n",
    "  features[\"mean_audio\"] = get_shape_and_set_modified_shape_2D(tensor = features[\"mean_audio\"], additional_dimension_sizes = [128])\n",
    "  print(\"serving_input_fn: features = {}\\n\".format(features))\n",
    "  \n",
    "  return tf.estimator.export.ServingInputReceiver(features = features, receiver_tensors = feature_placeholders)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Create custom estimator's train and evaluate function\n",
    "def train_and_evaluate(args):\n",
    "  # Create our custome estimator using our model function\n",
    "  estimator = tf.estimator.Estimator(\n",
    "    model_fn = video_level_model, \n",
    "    model_dir = args['output_dir'],\n",
    "    params = {'hidden_units': args['hidden_units'], 'top_k': args['top_k']})\n",
    "  # Create train spec to read in our training data\n",
    "  train_spec = tf.estimator.TrainSpec(\n",
    "    input_fn = read_dataset_video(\n",
    "      file_pattern = args['train_file_pattern'], \n",
    "      mode = tf.estimator.ModeKeys.TRAIN, \n",
    "      batch_size = args['batch_size']),\n",
    "    max_steps = args['train_steps'])\n",
    "  # Create exporter to save out the complete model to disk\n",
    "  exporter = tf.estimator.LatestExporter(name = 'exporter', serving_input_receiver_fn = serving_input_fn)\n",
    "  # Create eval spec to read in our validation data and export our model\n",
    "  eval_spec = tf.estimator.EvalSpec(\n",
    "    input_fn = read_dataset_video(\n",
    "      file_pattern = args['eval_file_pattern'], \n",
    "      mode = tf.estimator.ModeKeys.EVAL, \n",
    "      batch_size = args['batch_size']),\n",
    "    steps = None,\n",
    "    exporters = exporter,\n",
    "    start_delay_secs = args['start_delay_secs'],\n",
    "    throttle_secs = args['throttle_secs'])\n",
    "  # Create train and evaluate loop to train and evaluate our estimator\n",
    "  tf.estimator.train_and_evaluate(estimator = estimator, train_spec = train_spec, eval_spec = eval_spec)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Using default config.\n",
      "INFO:tensorflow:Using config: {'_save_checkpoints_secs': 600, '_session_config': None, '_keep_checkpoint_max': 5, '_task_type': 'worker', '_train_distribute': None, '_is_chief': True, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f7f238cd690>, '_evaluation_master': '', '_save_checkpoints_steps': None, '_keep_checkpoint_every_n_hours': 10000, '_service': None, '_num_ps_replicas': 0, '_tf_random_seed': None, '_master': '', '_num_worker_replicas': 1, '_task_id': 0, '_log_step_count_steps': 100, '_model_dir': 'trained_model', '_global_id_in_cluster': 0, '_save_summary_steps': 100}\n",
      "INFO:tensorflow:Running training and evaluation locally (non-distributed).\n",
      "INFO:tensorflow:Start train and evaluate loop. The evaluate will happen after 30 secs (eval_spec.throttle_secs) or training is finished.\n",
      "\n",
      "read_dataset_video: _input_fn: file_pattern = gs://youtube-8m-team/1/video_level/train/train*.tfrecord\n",
      "read_dataset_video: _input_fn: mode = train\n",
      "read_dataset_video: _input_fn: batch_size = 10\n",
      "read_dataset_video: _input_fn: dataset.TFRecordDataset = <TFRecordDataset shapes: (), types: tf.string>\n",
      "\n",
      "read_dataset_video: _input_fn: decode_example: features = {'labels': <tensorflow.python.framework.sparse_tensor.SparseTensor object at 0x7f7ed25ff4d0>, 'video_id': <tf.Tensor 'ParseSingleExample/ParseSingleExample:5' shape=() dtype=string>, 'mean_audio': <tf.Tensor 'ParseSingleExample/ParseSingleExample:3' shape=(128,) dtype=float32>, 'mean_rgb': <tf.Tensor 'ParseSingleExample/ParseSingleExample:4' shape=(1024,) dtype=float32>}\n",
      "read_dataset_video: _input_fn: decode_example: sparse_labels = SparseTensor(indices=Tensor(\"ParseSingleExample/ParseSingleExample:0\", shape=(?, 1), dtype=int64), values=Tensor(\"ParseSingleExample/ParseSingleExample:1\", shape=(?,), dtype=int64), dense_shape=Tensor(\"ParseSingleExample/ParseSingleExample:2\", shape=(1,), dtype=int64))\n",
      "\n",
      "read_dataset_video: _input_fn: decode_example: labels = Tensor(\"Cast:0\", shape=(4716,), dtype=float32)\n",
      "\n",
      "read_dataset_video: _input_fn: dataset.map = <MapDataset shapes: ({video_id: (), mean_audio: (128,), mean_rgb: (1024,)}, (4716,)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: dataset.shuffle = <ShuffleDataset shapes: ({video_id: (), mean_audio: (128,), mean_rgb: (1024,)}, (4716,)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: dataset.repeat = <RepeatDataset shapes: ({video_id: (), mean_audio: (128,), mean_rgb: (1024,)}, (4716,)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: dataset.batch = <BatchDataset shapes: ({video_id: (?,), mean_audio: (?, 128), mean_rgb: (?, 1024)}, (?, 4716)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: batch_features = {'video_id': <tf.Tensor 'IteratorGetNext:2' shape=(?,) dtype=string>, 'mean_audio': <tf.Tensor 'IteratorGetNext:0' shape=(?, 128) dtype=float32>, 'mean_rgb': <tf.Tensor 'IteratorGetNext:1' shape=(?, 1024) dtype=float32>}\n",
      "read_dataset_video: _input_fn: batch_labels = Tensor(\"IteratorGetNext:3\", shape=(?, 4716), dtype=float32, device=/device:CPU:0)\n",
      "\n",
      "INFO:tensorflow:Calling model_fn.\n",
      "\n",
      "video_level_model: features = {'video_id': <tf.Tensor 'IteratorGetNext:2' shape=(?,) dtype=string>, 'mean_audio': <tf.Tensor 'IteratorGetNext:0' shape=(?, 128) dtype=float32>, 'mean_rgb': <tf.Tensor 'IteratorGetNext:1' shape=(?, 1024) dtype=float32>}\n",
      "video_level_model: labels = Tensor(\"IteratorGetNext:3\", shape=(?, 4716), dtype=float32, device=/device:CPU:0)\n",
      "video_level_model: mode = train\n",
      "video_level_model: current_batch_size = Tensor(\"strided_slice:0\", shape=(), dtype=int32)\n",
      "video_level_model: combined_features = Tensor(\"concat:0\", shape=(?, 1152), dtype=float32)\n",
      "video_level_model: network = combined_features = Tensor(\"concat:0\", shape=(?, 1152), dtype=float32)\n",
      "video_level_model: network = Tensor(\"dense/Relu:0\", shape=(?, 1024), dtype=float32), units = 1024\n",
      "video_level_model: network = Tensor(\"dense_1/Relu:0\", shape=(?, 256), dtype=float32), units = 256\n",
      "video_level_model: network = Tensor(\"dense_2/Relu:0\", shape=(?, 64), dtype=float32), units = 64\n",
      "video_level_model: logits = Tensor(\"dense_3/BiasAdd:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_logits = TopKV2(values=<tf.Tensor 'TopKV2:0' shape=(?, 5) dtype=float32>, indices=<tf.Tensor 'TopKV2:1' shape=(?, 5) dtype=int32>)\n",
      "video_level_model: probabilities = Tensor(\"Sigmoid:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_probabilities = Tensor(\"Sigmoid_1:0\", shape=(?, 5), dtype=float32)\n",
      "video_level_model: top_k_classes = Tensor(\"TopKV2:1\", shape=(?, 5), dtype=int32)\n",
      "video_level_model: predictions = Tensor(\"Select:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_predictions = Tensor(\"Select_1:0\", shape=(?, 5), dtype=float32)\n",
      "\n",
      "INFO:tensorflow:Done calling model_fn.\n",
      "INFO:tensorflow:Create CheckpointSaverHook.\n",
      "INFO:tensorflow:Graph was finalized.\n",
      "INFO:tensorflow:Running local_init_op.\n",
      "INFO:tensorflow:Done running local_init_op.\n",
      "INFO:tensorflow:Saving checkpoints for 1 into trained_model/model.ckpt.\n",
      "INFO:tensorflow:loss = 0.6934132, step = 1\n",
      "INFO:tensorflow:Saving checkpoints for 100 into trained_model/model.ckpt.\n",
      "INFO:tensorflow:Loss for final step: 0.00912882.\n",
      "\n",
      "read_dataset_video: _input_fn: file_pattern = gs://youtube-8m-team/1/video_level/validate/validate-0.tfrecord\n",
      "read_dataset_video: _input_fn: mode = eval\n",
      "read_dataset_video: _input_fn: batch_size = 10\n",
      "read_dataset_video: _input_fn: dataset.TFRecordDataset = <TFRecordDataset shapes: (), types: tf.string>\n",
      "\n",
      "read_dataset_video: _input_fn: decode_example: features = {'labels': <tensorflow.python.framework.sparse_tensor.SparseTensor object at 0x7f7ed55d51d0>, 'video_id': <tf.Tensor 'ParseSingleExample/ParseSingleExample:5' shape=() dtype=string>, 'mean_audio': <tf.Tensor 'ParseSingleExample/ParseSingleExample:3' shape=(128,) dtype=float32>, 'mean_rgb': <tf.Tensor 'ParseSingleExample/ParseSingleExample:4' shape=(1024,) dtype=float32>}\n",
      "read_dataset_video: _input_fn: decode_example: sparse_labels = SparseTensor(indices=Tensor(\"ParseSingleExample/ParseSingleExample:0\", shape=(?, 1), dtype=int64), values=Tensor(\"ParseSingleExample/ParseSingleExample:1\", shape=(?,), dtype=int64), dense_shape=Tensor(\"ParseSingleExample/ParseSingleExample:2\", shape=(1,), dtype=int64))\n",
      "\n",
      "read_dataset_video: _input_fn: decode_example: labels = Tensor(\"Cast:0\", shape=(4716,), dtype=float32)\n",
      "\n",
      "read_dataset_video: _input_fn: dataset.map = <MapDataset shapes: ({video_id: (), mean_audio: (128,), mean_rgb: (1024,)}, (4716,)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: dataset.repeat = <RepeatDataset shapes: ({video_id: (), mean_audio: (128,), mean_rgb: (1024,)}, (4716,)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: dataset.batch = <BatchDataset shapes: ({video_id: (?,), mean_audio: (?, 128), mean_rgb: (?, 1024)}, (?, 4716)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: batch_features = {'video_id': <tf.Tensor 'IteratorGetNext:2' shape=(?,) dtype=string>, 'mean_audio': <tf.Tensor 'IteratorGetNext:0' shape=(?, 128) dtype=float32>, 'mean_rgb': <tf.Tensor 'IteratorGetNext:1' shape=(?, 1024) dtype=float32>}\n",
      "read_dataset_video: _input_fn: batch_labels = Tensor(\"IteratorGetNext:3\", shape=(?, 4716), dtype=float32, device=/device:CPU:0)\n",
      "\n",
      "INFO:tensorflow:Calling model_fn.\n",
      "\n",
      "video_level_model: features = {'video_id': <tf.Tensor 'IteratorGetNext:2' shape=(?,) dtype=string>, 'mean_audio': <tf.Tensor 'IteratorGetNext:0' shape=(?, 128) dtype=float32>, 'mean_rgb': <tf.Tensor 'IteratorGetNext:1' shape=(?, 1024) dtype=float32>}\n",
      "video_level_model: labels = Tensor(\"IteratorGetNext:3\", shape=(?, 4716), dtype=float32, device=/device:CPU:0)\n",
      "video_level_model: mode = eval\n",
      "video_level_model: current_batch_size = Tensor(\"strided_slice:0\", shape=(), dtype=int32)\n",
      "video_level_model: combined_features = Tensor(\"concat:0\", shape=(?, 1152), dtype=float32)\n",
      "video_level_model: network = combined_features = Tensor(\"concat:0\", shape=(?, 1152), dtype=float32)\n",
      "video_level_model: network = Tensor(\"dense/Relu:0\", shape=(?, 1024), dtype=float32), units = 1024\n",
      "video_level_model: network = Tensor(\"dense_1/Relu:0\", shape=(?, 256), dtype=float32), units = 256\n",
      "video_level_model: network = Tensor(\"dense_2/Relu:0\", shape=(?, 64), dtype=float32), units = 64\n",
      "video_level_model: logits = Tensor(\"dense_3/BiasAdd:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_logits = TopKV2(values=<tf.Tensor 'TopKV2:0' shape=(?, 5) dtype=float32>, indices=<tf.Tensor 'TopKV2:1' shape=(?, 5) dtype=int32>)\n",
      "video_level_model: probabilities = Tensor(\"Sigmoid:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_probabilities = Tensor(\"Sigmoid_1:0\", shape=(?, 5), dtype=float32)\n",
      "video_level_model: top_k_classes = Tensor(\"TopKV2:1\", shape=(?, 5), dtype=int32)\n",
      "video_level_model: predictions = Tensor(\"Select:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_predictions = Tensor(\"Select_1:0\", shape=(?, 5), dtype=float32)\n",
      "\n",
      "INFO:tensorflow:Done calling model_fn.\n",
      "INFO:tensorflow:Starting evaluation at 2018-05-25-05:06:32\n",
      "INFO:tensorflow:Graph was finalized.\n",
      "INFO:tensorflow:Restoring parameters from trained_model/model.ckpt-100\n",
      "INFO:tensorflow:Running local_init_op.\n",
      "INFO:tensorflow:Done running local_init_op.\n",
      "INFO:tensorflow:Finished evaluation at 2018-05-25-05:06:33\n",
      "INFO:tensorflow:Saving dict for global step 100: accuracy = 0.00032226433, global_step = 100, loss = 0.00826398\n",
      "\n",
      "serving_input_fn: feature_placeholders = {'video_id': <tf.Tensor 'Placeholder:0' shape=(?,) dtype=string>, 'mean_audio': <tf.Tensor 'Placeholder_2:0' shape=(?,) dtype=string>, 'mean_rgb': <tf.Tensor 'Placeholder_1:0' shape=(?,) dtype=string>}\n",
      "serving_input_fn: fix_shape_and_type_for_serving: split_string = Tensor(\"map/TensorArrayStack/TensorArrayGatherV3:0\", shape=(?, ?), dtype=string)\n",
      "serving_input_fn: fix_shape_and_type_for_serving: feature_tensor = Tensor(\"StringToNumber:0\", shape=(?, ?), dtype=float32)\n",
      "serving_input_fn: fix_shape_and_type_for_serving: split_string = Tensor(\"map_1/TensorArrayStack/TensorArrayGatherV3:0\", shape=(?, ?), dtype=string)\n",
      "serving_input_fn: fix_shape_and_type_for_serving: feature_tensor = Tensor(\"StringToNumber_1:0\", shape=(?, ?), dtype=float32)\n",
      "serving_input_fn: features = {'video_id': <tf.Tensor 'Placeholder:0' shape=(?,) dtype=string>, 'mean_audio': <tf.Tensor 'StringToNumber_1:0' shape=(?, ?) dtype=float32>, 'mean_rgb': <tf.Tensor 'StringToNumber:0' shape=(?, ?) dtype=float32>}\n",
      "serving_input_fn: get_shape_and_set_modified_shape_2D: tensor = Tensor(\"StringToNumber:0\", shape=(?, 1024), dtype=float32), additional_dimension_sizes = [1024]\n",
      "serving_input_fn: get_shape_and_set_modified_shape_2D: tensor = Tensor(\"StringToNumber_1:0\", shape=(?, 128), dtype=float32), additional_dimension_sizes = [128]\n",
      "serving_input_fn: features = {'video_id': <tf.Tensor 'Placeholder:0' shape=(?,) dtype=string>, 'mean_audio': <tf.Tensor 'StringToNumber_1:0' shape=(?, 128) dtype=float32>, 'mean_rgb': <tf.Tensor 'StringToNumber:0' shape=(?, 1024) dtype=float32>}\n",
      "\n",
      "INFO:tensorflow:Calling model_fn.\n",
      "\n",
      "video_level_model: features = {'video_id': <tf.Tensor 'Placeholder:0' shape=(?,) dtype=string>, 'mean_audio': <tf.Tensor 'StringToNumber_1:0' shape=(?, 128) dtype=float32>, 'mean_rgb': <tf.Tensor 'StringToNumber:0' shape=(?, 1024) dtype=float32>}\n",
      "video_level_model: labels = None\n",
      "video_level_model: mode = infer\n",
      "video_level_model: current_batch_size = Tensor(\"strided_slice_2:0\", shape=(), dtype=int32)\n",
      "video_level_model: combined_features = Tensor(\"concat:0\", shape=(?, 1152), dtype=float32)\n",
      "video_level_model: network = combined_features = Tensor(\"concat:0\", shape=(?, 1152), dtype=float32)\n",
      "video_level_model: network = Tensor(\"dense/Relu:0\", shape=(?, 1024), dtype=float32), units = 1024\n",
      "video_level_model: network = Tensor(\"dense_1/Relu:0\", shape=(?, 256), dtype=float32), units = 256\n",
      "video_level_model: network = Tensor(\"dense_2/Relu:0\", shape=(?, 64), dtype=float32), units = 64\n",
      "video_level_model: logits = Tensor(\"dense_3/BiasAdd:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_logits = TopKV2(values=<tf.Tensor 'TopKV2:0' shape=(?, 5) dtype=float32>, indices=<tf.Tensor 'TopKV2:1' shape=(?, 5) dtype=int32>)\n",
      "video_level_model: probabilities = Tensor(\"Sigmoid:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_probabilities = Tensor(\"Sigmoid_1:0\", shape=(?, 5), dtype=float32)\n",
      "video_level_model: top_k_classes = Tensor(\"TopKV2:1\", shape=(?, 5), dtype=int32)\n",
      "video_level_model: predictions = Tensor(\"Select:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_predictions = Tensor(\"Select_1:0\", shape=(?, 5), dtype=float32)\n",
      "\n",
      "INFO:tensorflow:Done calling model_fn.\n",
      "INFO:tensorflow:Signatures INCLUDED in export for Classify: None\n",
      "INFO:tensorflow:Signatures INCLUDED in export for Regress: None\n",
      "INFO:tensorflow:Signatures INCLUDED in export for Predict: ['serving_default', 'predict_export_outputs']\n",
      "INFO:tensorflow:Restoring parameters from trained_model/model.ckpt-100\n",
      "INFO:tensorflow:Assets added to graph.\n",
      "INFO:tensorflow:No assets to write.\n",
      "INFO:tensorflow:SavedModel written to: trained_model/export/exporter/temp-1527224793/saved_model.pb\n"
     ]
    }
   ],
   "source": [
    "# Run the training job\n",
    "shutil.rmtree(arguments['output_dir'], ignore_errors = True) # start fresh each time\n",
    "train_and_evaluate(args = arguments)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Training"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Locally"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "read_dataset_video: _input_fn: file_pattern = gs://youtube-8m-team/1/video_level/train/train*.tfrecord\n",
      "read_dataset_video: _input_fn: mode = train\n",
      "read_dataset_video: _input_fn: batch_size = 10\n",
      "read_dataset_video: _input_fn: dataset.TFRecordDataset = <TFRecordDataset shapes: (), types: tf.string>\n",
      "\n",
      "read_dataset_video: _input_fn: decode_example: features = {'labels': <tensorflow.python.framework.sparse_tensor.SparseTensor object at 0x7f4307390610>, 'video_id': <tf.Tensor 'ParseSingleExample/ParseSingleExample:5' shape=() dtype=string>, 'mean_audio': <tf.Tensor 'ParseSingleExample/ParseSingleExample:3' shape=(128,) dtype=float32>, 'mean_rgb': <tf.Tensor 'ParseSingleExample/ParseSingleExample:4' shape=(1024,) dtype=float32>}\n",
      "read_dataset_video: _input_fn: decode_example: sparse_labels = SparseTensor(indices=Tensor(\"ParseSingleExample/ParseSingleExample:0\", shape=(?, 1), dtype=int64), values=Tensor(\"ParseSingleExample/ParseSingleExample:1\", shape=(?,), dtype=int64), dense_shape=Tensor(\"ParseSingleExample/ParseSingleExample:2\", shape=(1,), dtype=int64))\n",
      "\n",
      "read_dataset_video: _input_fn: decode_example: labels = Tensor(\"Cast:0\", shape=(4716,), dtype=float32)\n",
      "\n",
      "read_dataset_video: _input_fn: dataset.map = <MapDataset shapes: ({video_id: (), mean_audio: (128,), mean_rgb: (1024,)}, (4716,)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: dataset.shuffle = <ShuffleDataset shapes: ({video_id: (), mean_audio: (128,), mean_rgb: (1024,)}, (4716,)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: dataset.repeat = <RepeatDataset shapes: ({video_id: (), mean_audio: (128,), mean_rgb: (1024,)}, (4716,)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: dataset.batch = <BatchDataset shapes: ({video_id: (?,), mean_audio: (?, 128), mean_rgb: (?, 1024)}, (?, 4716)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: batch_features = {'video_id': <tf.Tensor 'IteratorGetNext:2' shape=(?,) dtype=string>, 'mean_audio': <tf.Tensor 'IteratorGetNext:0' shape=(?, 128) dtype=float32>, 'mean_rgb': <tf.Tensor 'IteratorGetNext:1' shape=(?, 1024) dtype=float32>}\n",
      "read_dataset_video: _input_fn: batch_labels = Tensor(\"IteratorGetNext:3\", shape=(?, 4716), dtype=float32, device=/device:CPU:0)\n",
      "\n",
      "\n",
      "video_level_model: features = {'video_id': <tf.Tensor 'IteratorGetNext:2' shape=(?,) dtype=string>, 'mean_audio': <tf.Tensor 'IteratorGetNext:0' shape=(?, 128) dtype=float32>, 'mean_rgb': <tf.Tensor 'IteratorGetNext:1' shape=(?, 1024) dtype=float32>}\n",
      "video_level_model: labels = Tensor(\"IteratorGetNext:3\", shape=(?, 4716), dtype=float32, device=/device:CPU:0)\n",
      "video_level_model: mode = train\n",
      "video_level_model: current_batch_size = Tensor(\"strided_slice:0\", shape=(), dtype=int32)\n",
      "video_level_model: combined_features = Tensor(\"concat:0\", shape=(?, 1152), dtype=float32)\n",
      "video_level_model: network = combined_features = Tensor(\"concat:0\", shape=(?, 1152), dtype=float32)\n",
      "video_level_model: network = Tensor(\"dense/Relu:0\", shape=(?, 1024), dtype=float32), units = 1024\n",
      "video_level_model: network = Tensor(\"dense_1/Relu:0\", shape=(?, 512), dtype=float32), units = 512\n",
      "video_level_model: network = Tensor(\"dense_2/Relu:0\", shape=(?, 256), dtype=float32), units = 256\n",
      "video_level_model: logits = Tensor(\"dense_3/BiasAdd:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_logits = TopKV2(values=<tf.Tensor 'TopKV2:0' shape=(?, 5) dtype=float32>, indices=<tf.Tensor 'TopKV2:1' shape=(?, 5) dtype=int32>)\n",
      "video_level_model: probabilities = Tensor(\"Sigmoid:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_probabilities = Tensor(\"Sigmoid_1:0\", shape=(?, 5), dtype=float32)\n",
      "video_level_model: top_k_classes = Tensor(\"TopKV2:1\", shape=(?, 5), dtype=int32)\n",
      "video_level_model: predictions = Tensor(\"Select:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_predictions = Tensor(\"Select_1:0\", shape=(?, 5), dtype=float32)\n",
      "\n",
      "\n",
      "read_dataset_video: _input_fn: file_pattern = gs://youtube-8m-team/1/video_level/validate/validate-0.tfrecord\n",
      "read_dataset_video: _input_fn: mode = eval\n",
      "read_dataset_video: _input_fn: batch_size = 10\n",
      "read_dataset_video: _input_fn: dataset.TFRecordDataset = <TFRecordDataset shapes: (), types: tf.string>\n",
      "\n",
      "read_dataset_video: _input_fn: decode_example: features = {'labels': <tensorflow.python.framework.sparse_tensor.SparseTensor object at 0x7f42ee4d3450>, 'video_id': <tf.Tensor 'ParseSingleExample/ParseSingleExample:5' shape=() dtype=string>, 'mean_audio': <tf.Tensor 'ParseSingleExample/ParseSingleExample:3' shape=(128,) dtype=float32>, 'mean_rgb': <tf.Tensor 'ParseSingleExample/ParseSingleExample:4' shape=(1024,) dtype=float32>}\n",
      "read_dataset_video: _input_fn: decode_example: sparse_labels = SparseTensor(indices=Tensor(\"ParseSingleExample/ParseSingleExample:0\", shape=(?, 1), dtype=int64), values=Tensor(\"ParseSingleExample/ParseSingleExample:1\", shape=(?,), dtype=int64), dense_shape=Tensor(\"ParseSingleExample/ParseSingleExample:2\", shape=(1,), dtype=int64))\n",
      "\n",
      "read_dataset_video: _input_fn: decode_example: labels = Tensor(\"Cast:0\", shape=(4716,), dtype=float32)\n",
      "\n",
      "read_dataset_video: _input_fn: dataset.map = <MapDataset shapes: ({video_id: (), mean_audio: (128,), mean_rgb: (1024,)}, (4716,)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: dataset.repeat = <RepeatDataset shapes: ({video_id: (), mean_audio: (128,), mean_rgb: (1024,)}, (4716,)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: dataset.batch = <BatchDataset shapes: ({video_id: (?,), mean_audio: (?, 128), mean_rgb: (?, 1024)}, (?, 4716)), types: ({video_id: tf.string, mean_audio: tf.float32, mean_rgb: tf.float32}, tf.float32)>\n",
      "read_dataset_video: _input_fn: batch_features = {'video_id': <tf.Tensor 'IteratorGetNext:2' shape=(?,) dtype=string>, 'mean_audio': <tf.Tensor 'IteratorGetNext:0' shape=(?, 128) dtype=float32>, 'mean_rgb': <tf.Tensor 'IteratorGetNext:1' shape=(?, 1024) dtype=float32>}\n",
      "read_dataset_video: _input_fn: batch_labels = Tensor(\"IteratorGetNext:3\", shape=(?, 4716), dtype=float32, device=/device:CPU:0)\n",
      "\n",
      "\n",
      "video_level_model: features = {'video_id': <tf.Tensor 'IteratorGetNext:2' shape=(?,) dtype=string>, 'mean_audio': <tf.Tensor 'IteratorGetNext:0' shape=(?, 128) dtype=float32>, 'mean_rgb': <tf.Tensor 'IteratorGetNext:1' shape=(?, 1024) dtype=float32>}\n",
      "video_level_model: labels = Tensor(\"IteratorGetNext:3\", shape=(?, 4716), dtype=float32, device=/device:CPU:0)\n",
      "video_level_model: mode = eval\n",
      "video_level_model: current_batch_size = Tensor(\"strided_slice:0\", shape=(), dtype=int32)\n",
      "video_level_model: combined_features = Tensor(\"concat:0\", shape=(?, 1152), dtype=float32)\n",
      "video_level_model: network = combined_features = Tensor(\"concat:0\", shape=(?, 1152), dtype=float32)\n",
      "video_level_model: network = Tensor(\"dense/Relu:0\", shape=(?, 1024), dtype=float32), units = 1024\n",
      "video_level_model: network = Tensor(\"dense_1/Relu:0\", shape=(?, 512), dtype=float32), units = 512\n",
      "video_level_model: network = Tensor(\"dense_2/Relu:0\", shape=(?, 256), dtype=float32), units = 256\n",
      "video_level_model: logits = Tensor(\"dense_3/BiasAdd:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_logits = TopKV2(values=<tf.Tensor 'TopKV2:0' shape=(?, 5) dtype=float32>, indices=<tf.Tensor 'TopKV2:1' shape=(?, 5) dtype=int32>)\n",
      "video_level_model: probabilities = Tensor(\"Sigmoid:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_probabilities = Tensor(\"Sigmoid_1:0\", shape=(?, 5), dtype=float32)\n",
      "video_level_model: top_k_classes = Tensor(\"TopKV2:1\", shape=(?, 5), dtype=int32)\n",
      "video_level_model: predictions = Tensor(\"Select:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_predictions = Tensor(\"Select_1:0\", shape=(?, 5), dtype=float32)\n",
      "\n",
      "\n",
      "serving_input_fn: feature_placeholders = {'video_id': <tf.Tensor 'Placeholder:0' shape=(?,) dtype=string>, 'mean_audio': <tf.Tensor 'Placeholder_2:0' shape=(?,) dtype=string>, 'mean_rgb': <tf.Tensor 'Placeholder_1:0' shape=(?,) dtype=string>}\n",
      "serving_input_fn: fix_shape_and_type_for_serving: split_string = Tensor(\"map/TensorArrayStack/TensorArrayGatherV3:0\", shape=(?, ?), dtype=string)\n",
      "serving_input_fn: fix_shape_and_type_for_serving: feature_tensor = Tensor(\"StringToNumber:0\", shape=(?, ?), dtype=float32)\n",
      "serving_input_fn: fix_shape_and_type_for_serving: split_string = Tensor(\"map_1/TensorArrayStack/TensorArrayGatherV3:0\", shape=(?, ?), dtype=string)\n",
      "serving_input_fn: fix_shape_and_type_for_serving: feature_tensor = Tensor(\"StringToNumber_1:0\", shape=(?, ?), dtype=float32)\n",
      "serving_input_fn: features = {'video_id': <tf.Tensor 'Placeholder:0' shape=(?,) dtype=string>, 'mean_audio': <tf.Tensor 'StringToNumber_1:0' shape=(?, ?) dtype=float32>, 'mean_rgb': <tf.Tensor 'StringToNumber:0' shape=(?, ?) dtype=float32>}\n",
      "serving_input_fn: get_shape_and_set_modified_shape_2D: tensor = Tensor(\"StringToNumber:0\", shape=(?, 1024), dtype=float32), additional_dimension_sizes = [1024]\n",
      "serving_input_fn: get_shape_and_set_modified_shape_2D: tensor = Tensor(\"StringToNumber_1:0\", shape=(?, 128), dtype=float32), additional_dimension_sizes = [128]\n",
      "serving_input_fn: features = {'video_id': <tf.Tensor 'Placeholder:0' shape=(?,) dtype=string>, 'mean_audio': <tf.Tensor 'StringToNumber_1:0' shape=(?, 128) dtype=float32>, 'mean_rgb': <tf.Tensor 'StringToNumber:0' shape=(?, 1024) dtype=float32>}\n",
      "\n",
      "\n",
      "video_level_model: features = {'video_id': <tf.Tensor 'Placeholder:0' shape=(?,) dtype=string>, 'mean_audio': <tf.Tensor 'StringToNumber_1:0' shape=(?, 128) dtype=float32>, 'mean_rgb': <tf.Tensor 'StringToNumber:0' shape=(?, 1024) dtype=float32>}\n",
      "video_level_model: labels = None\n",
      "video_level_model: mode = infer\n",
      "video_level_model: current_batch_size = Tensor(\"strided_slice_2:0\", shape=(), dtype=int32)\n",
      "video_level_model: combined_features = Tensor(\"concat:0\", shape=(?, 1152), dtype=float32)\n",
      "video_level_model: network = combined_features = Tensor(\"concat:0\", shape=(?, 1152), dtype=float32)\n",
      "video_level_model: network = Tensor(\"dense/Relu:0\", shape=(?, 1024), dtype=float32), units = 1024\n",
      "video_level_model: network = Tensor(\"dense_1/Relu:0\", shape=(?, 512), dtype=float32), units = 512\n",
      "video_level_model: network = Tensor(\"dense_2/Relu:0\", shape=(?, 256), dtype=float32), units = 256\n",
      "video_level_model: logits = Tensor(\"dense_3/BiasAdd:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_logits = TopKV2(values=<tf.Tensor 'TopKV2:0' shape=(?, 5) dtype=float32>, indices=<tf.Tensor 'TopKV2:1' shape=(?, 5) dtype=int32>)\n",
      "video_level_model: probabilities = Tensor(\"Sigmoid:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_probabilities = Tensor(\"Sigmoid_1:0\", shape=(?, 5), dtype=float32)\n",
      "video_level_model: top_k_classes = Tensor(\"TopKV2:1\", shape=(?, 5), dtype=int32)\n",
      "video_level_model: predictions = Tensor(\"Select:0\", shape=(?, 4716), dtype=float32)\n",
      "video_level_model: top_k_predictions = Tensor(\"Select_1:0\", shape=(?, 5), dtype=float32)\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/envs/py2env/lib/python2.7/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n",
      "INFO:tensorflow:Using default config.\n",
      "INFO:tensorflow:Using config: {'_save_checkpoints_secs': 600, '_session_config': None, '_keep_checkpoint_max': 5, '_task_type': 'worker', '_train_distribute': None, '_is_chief': True, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f4307444f90>, '_evaluation_master': '', '_save_checkpoints_steps': None, '_keep_checkpoint_every_n_hours': 10000, '_service': None, '_num_ps_replicas': 0, '_tf_random_seed': None, '_master': '', '_num_worker_replicas': 1, '_task_id': 0, '_log_step_count_steps': 100, '_model_dir': 'trained_model/', '_global_id_in_cluster': 0, '_save_summary_steps': 100}\n",
      "INFO:tensorflow:Running training and evaluation locally (non-distributed).\n",
      "INFO:tensorflow:Start train and evaluate loop. The evaluate will happen after 30 secs (eval_spec.throttle_secs) or training is finished.\n",
      "INFO:tensorflow:Calling model_fn.\n",
      "INFO:tensorflow:Done calling model_fn.\n",
      "INFO:tensorflow:Create CheckpointSaverHook.\n",
      "INFO:tensorflow:Graph was finalized.\n",
      "2018-05-25 05:07:31.691551: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA\n",
      "INFO:tensorflow:Running local_init_op.\n",
      "INFO:tensorflow:Done running local_init_op.\n",
      "INFO:tensorflow:Saving checkpoints for 1 into trained_model/model.ckpt.\n",
      "INFO:tensorflow:loss = 0.6933336, step = 1\n",
      "INFO:tensorflow:Saving checkpoints for 100 into trained_model/model.ckpt.\n",
      "INFO:tensorflow:Loss for final step: 0.0069382903.\n",
      "INFO:tensorflow:Calling model_fn.\n",
      "INFO:tensorflow:Done calling model_fn.\n",
      "INFO:tensorflow:Starting evaluation at 2018-05-25-05:07:46\n",
      "INFO:tensorflow:Graph was finalized.\n",
      "INFO:tensorflow:Restoring parameters from trained_model/model.ckpt-100\n",
      "INFO:tensorflow:Running local_init_op.\n",
      "INFO:tensorflow:Done running local_init_op.\n",
      "INFO:tensorflow:Finished evaluation at 2018-05-25-05:07:48\n",
      "INFO:tensorflow:Saving dict for global step 100: accuracy = 0.00032125626, global_step = 100, loss = 0.008560455\n",
      "INFO:tensorflow:Calling model_fn.\n",
      "INFO:tensorflow:Done calling model_fn.\n",
      "INFO:tensorflow:Signatures INCLUDED in export for Classify: None\n",
      "INFO:tensorflow:Signatures INCLUDED in export for Regress: None\n",
      "INFO:tensorflow:Signatures INCLUDED in export for Predict: ['serving_default', 'predict_export_outputs']\n",
      "INFO:tensorflow:Restoring parameters from trained_model/model.ckpt-100\n",
      "INFO:tensorflow:Assets added to graph.\n",
      "INFO:tensorflow:No assets to write.\n",
      "INFO:tensorflow:SavedModel written to: trained_model/export/exporter/temp-1527224870/saved_model.pb\n"
     ]
    }
   ],
   "source": [
    "%bash\n",
    "OUTDIR=trained_model\n",
    "rm -rf $OUTDIR\n",
    "export PYTHONPATH=$PYTHONPATH:$PWD/trainer\n",
    "python -m trainer.task \\\n",
    "  --train_file_pattern=\"gs://youtube-8m-team/1/video_level/train/train*.tfrecord\" \\\n",
    "  --eval_file_pattern=\"gs://youtube-8m-team/1/video_level/validate/validate-0.tfrecord\"  \\\n",
    "  --output_dir=$OUTDIR \\\n",
    "  --batch_size=10 \\\n",
    "  --train_steps=100 \\\n",
    "  --hidden_units=\"1024 512 256\" \\\n",
    "  --top_k=5 \\\n",
    "  --job-dir=./tmp"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### GCloud"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gs://youtube8m-4-train/youtube_8m_video_level_datasets/trained_model us-central1 job_youtube_8m_video_level_datasets180525_002728\n",
      "jobId: job_youtube_8m_video_level_datasets180525_002728\n",
      "state: QUEUED\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "CommandException: 1 files/objects could not be removed.\n",
      "Job [job_youtube_8m_video_level_datasets180525_002728] submitted successfully.\n",
      "Your job is still active. You may view the status of your job with the command\n",
      "\n",
      "  $ gcloud ml-engine jobs describe job_youtube_8m_video_level_datasets180525_002728\n",
      "\n",
      "or continue streaming the logs with the command\n",
      "\n",
      "  $ gcloud ml-engine jobs stream-logs job_youtube_8m_video_level_datasets180525_002728\n"
     ]
    }
   ],
   "source": [
    "%bash\n",
    "OUTDIR=gs://$BUCKET/youtube_8m_video_level_datasets/trained_model\n",
    "JOBNAME=job_youtube_8m_video_level_datasets$(date -u +%y%m%d_%H%M%S)\n",
    "echo $OUTDIR $REGION $JOBNAME\n",
    "gcloud storage rm --recursive --continue-on-error $OUTDIR\n",    "gcloud ml-engine jobs submit training $JOBNAME \\\n",
    "  --region=$REGION \\\n",
    "  --module-name=trainer.task \\\n",
    "  --package-path=$PWD/trainer \\\n",
    "  --job-dir=$OUTDIR \\\n",
    "  --staging-bucket=gs://$BUCKET \\\n",
    "  --scale-tier=STANDARD_1 \\\n",
    "  --runtime-version=1.5 \\\n",
    "  -- \\\n",
    "  --train_file_pattern=\"gs://youtube-8m-team/1/video_level/train/train*.tfrecord\" \\\n",
    "  --eval_file_pattern=\"gs://youtube-8m-team/1/video_level/validate/validate-0.tfrecord\"  \\\n",
    "  --output_dir=$OUTDIR \\\n",
    "  --batch_size=50 \\\n",
    "  --train_steps=10000 \\\n",
    "  --hidden_units=\"1024 512 256\" \\\n",
    "  --top_k=5 \\\n",
    "  --job-dir=$OUTDIR"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hyperparameter tuning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Writing hyperparam.yaml\n"
     ]
    }
   ],
   "source": [
    "%writefile hyperparam.yaml\n",
    "trainingInput:\n",
    "  scaleTier: STANDARD_1\n",
    "  hyperparameters:\n",
    "    hyperparameterMetricTag: accuracy\n",
    "    goal: MAXIMIZE\n",
    "    maxTrials: 30\n",
    "    maxParallelTrials: 1\n",
    "    params:\n",
    "    - parameterName: batch_size\n",
    "      type: INTEGER\n",
    "      minValue: 8\n",
    "      maxValue: 512\n",
    "      scaleType: UNIT_LOG_SCALE\n",
    "    - parameterName: hidden_units\n",
    "      type: CATEGORICAL\n",
    "      categoricalValues: [\"64 32\", \"256 128 16\", \"64 64 64 8\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gs://youtube8m-4-train/youtube_8m_video_level_datasets/hyperparam us-central1 job_youtube_8m_video_level_datasets180525_061024\n",
      "jobId: job_youtube_8m_video_level_datasets180525_061024\n",
      "state: QUEUED\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "CommandException: 1 files/objects could not be removed.\n",
      "Job [job_youtube_8m_video_level_datasets180525_061024] submitted successfully.\n",
      "Your job is still active. You may view the status of your job with the command\n",
      "\n",
      "  $ gcloud ml-engine jobs describe job_youtube_8m_video_level_datasets180525_061024\n",
      "\n",
      "or continue streaming the logs with the command\n",
      "\n",
      "  $ gcloud ml-engine jobs stream-logs job_youtube_8m_video_level_datasets180525_061024\n"
     ]
    }
   ],
   "source": [
    "%bash\n",
    "OUTDIR=gs://$BUCKET/youtube_8m_video_level_datasets/hyperparam\n",
    "JOBNAME=job_youtube_8m_video_level_datasets$(date -u +%y%m%d_%H%M%S)\n",
    "echo $OUTDIR $REGION $JOBNAME\n",
    "gcloud storage rm --recursive --continue-on-error $OUTDIR\n",    "gcloud ml-engine jobs submit training $JOBNAME \\\n",
    "  --region=$REGION \\\n",
    "  --module-name=trainer.task \\\n",
    "  --package-path=$PWD/trainer \\\n",
    "  --job-dir=$OUTDIR \\\n",
    "  --staging-bucket=gs://$BUCKET \\\n",
    "  --scale-tier=STANDARD_1 \\\n",
    "  --config=hyperparam.yaml \\\n",
    "  --runtime-version=1.5 \\\n",
    "  -- \\\n",
    "  --train_file_pattern=\"gs://youtube-8m-team/1/video_level/train/train*.tfrecord\" \\\n",
    "  --eval_file_pattern=\"gs://youtube-8m-team/1/video_level/validate/validate-0.tfrecord\"  \\\n",
    "  --output_dir=$OUTDIR \\\n",
    "  --train_steps=10000 \\\n",
    "  --top_k=5 \\\n",
    "  --job-dir=$OUTDIR"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Deploy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Deleting and deploying youtube_8m_video_level_datasets v1 from gs://youtube8m-4-train/youtube_8m_video_level_datasets/trained_model/export/exporter/1527208584/ ... this will take a few minutes\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Created ml engine model [projects/qwiklabs-gcp-8d3d0cd07cef9252/models/youtube_8m_video_level_datasets].\n",
      "Creating version (this might take a few minutes)......\n",
      "..............................................................................................................done.\n"
     ]
    }
   ],
   "source": [
    "%bash\n",
    "MODEL_NAME=\"youtube_8m_video_level_datasets\"\n",
    "MODEL_VERSION=\"v1\"\n",
    "MODEL_LOCATION=$(gcloud storage ls gs://$BUCKET/youtube_8m_video_level_datasets/trained_model/export/exporter/ | tail -1)\n",    "echo \"Deleting and deploying $MODEL_NAME $MODEL_VERSION from $MODEL_LOCATION ... this will take a few minutes\"\n",
    "#gcloud ml-engine versions delete ${MODEL_VERSION} --model ${MODEL_NAME}\n",
    "#gcloud ml-engine models delete ${MODEL_NAME}\n",
    "gcloud ml-engine models create $MODEL_NAME --regions $REGION\n",
    "gcloud ml-engine versions create $MODEL_VERSION --model $MODEL_NAME --origin $MODEL_LOCATION --runtime-version 1.5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Prediction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Prep"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Let's call our input function to decode our data to put into BigQuery for testing predictions\n",
    "video_list = []\n",
    "with tf.Session() as sess:\n",
    "  fn = read_dataset_video(\n",
    "    file_pattern = \"gs://youtube-8m-team/1/video_level/validate/validate-0.tfrecord\", \n",
    "    mode = tf.estimator.ModeKeys.EVAL, \n",
    "    batch_size = 1)\n",
    "  batch_features, batch_labels = fn()\n",
    "  for key,value in batch_features.items():\n",
    "    batch_features[key] = tf.squeeze(batch_features[key])\n",
    "  fixed_batch_features = batch_features\n",
    "  fixed_batch_labels = tf.squeeze(batch_labels)\n",
    "\n",
    "  while True:\n",
    "    features, labels = sess.run([fixed_batch_features, fixed_batch_labels])\n",
    "    features[\"labels\"] = labels\n",
    "    video_list.append(features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "331"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This is the number of videos from the video level file we just processed\n",
    "len(video_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Convert the nd-arrays to lists and cast to strings (video_id is already a single string)\n",
    "for items in video_list:\n",
    "  items[\"labels\"] = str(items[\"labels\"].tolist())\n",
    "  items[\"mean_rgb\"] = str(items[\"mean_rgb\"].tolist())\n",
    "  items[\"mean_audio\"] = str(items[\"mean_audio\"].tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>video_id</th>\n",
       "      <th>mean_rgb</th>\n",
       "      <th>mean_audio</th>\n",
       "      <th>labels</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0AjrnQ0N3A</td>\n",
       "      <td>[0.31275367736816406, -0.0275861918926239, -0....</td>\n",
       "      <td>[-1.3102529048919678, -0.16714175045490265, 0....</td>\n",
       "      <td>[1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0MpgkddrY4</td>\n",
       "      <td>[0.3996831178665161, -0.7902982831001282, 1.85...</td>\n",
       "      <td>[1.4524954557418823, 1.5982519388198853, 1.783...</td>\n",
       "      <td>[0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-02RMEBtLDo</td>\n",
       "      <td>[-0.5323705077171326, -0.18418750166893005, 1....</td>\n",
       "      <td>[-0.3671940267086029, 0.43636152148246765, 1.7...</td>\n",
       "      <td>[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-00LLAtj0JE</td>\n",
       "      <td>[-0.12762920558452606, -0.9175933599472046, -0...</td>\n",
       "      <td>[0.5460372567176819, 1.4538171291351318, -1.59...</td>\n",
       "      <td>[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-07wapPiIAg</td>\n",
       "      <td>[-1.5168684720993042, 1.3144418001174927, 0.65...</td>\n",
       "      <td>[0.9732653498649597, -0.26707080006599426, -0....</td>\n",
       "      <td>[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      video_id                                           mean_rgb  \\\n",
       "0  -0AjrnQ0N3A  [0.31275367736816406, -0.0275861918926239, -0....   \n",
       "1  -0MpgkddrY4  [0.3996831178665161, -0.7902982831001282, 1.85...   \n",
       "2  -02RMEBtLDo  [-0.5323705077171326, -0.18418750166893005, 1....   \n",
       "3  -00LLAtj0JE  [-0.12762920558452606, -0.9175933599472046, -0...   \n",
       "4  -07wapPiIAg  [-1.5168684720993042, 1.3144418001174927, 0.65...   \n",
       "\n",
       "                                          mean_audio  \\\n",
       "0  [-1.3102529048919678, -0.16714175045490265, 0....   \n",
       "1  [1.4524954557418823, 1.5982519388198853, 1.783...   \n",
       "2  [-0.3671940267086029, 0.43636152148246765, 1.7...   \n",
       "3  [0.5460372567176819, 1.4538171291351318, -1.59...   \n",
       "4  [0.9732653498649597, -0.26707080006599426, -0....   \n",
       "\n",
       "                                              labels  \n",
       "0  [1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, ...  \n",
       "1  [0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, ...  \n",
       "2  [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...  \n",
       "3  [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...  \n",
       "4  [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a dataframe from the list\n",
    "video_df = pd.DataFrame(video_list)\n",
    "video_df = video_df[[\"video_id\", \"mean_rgb\", \"mean_audio\", \"labels\"]]\n",
    "video_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\n",
      "Load is 100% Complete\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Export dataframe to BigQuery\n",
    "import datalab.bigquery as bq\n",
    "bigquery_dataset_name = 'ryan_youtube'\n",
    "bigquery_table_name = 'tbl_video_level'\n",
    "\n",
    "# Define BigQuery dataset and table\\n\",\n",
    "dataset = bq.Dataset(bigquery_dataset_name)\n",
    "table = bq.Table(bigquery_dataset_name + '.' + bigquery_table_name)\n",
    "\n",
    "# Create BigQuery dataset\n",
    "if not dataset.exists():\n",
    "    dataset.create()\n",
    "\n",
    "# Create or overwrite the existing table if it exists\\n\",\n",
    "table_schema = bq.Schema.from_dataframe(video_df)\n",
    "table.create(schema = table_schema, overwrite = True)\n",
    "\n",
    "video_df.to_gbq(destination_table = bigquery_dataset_name + '.' + bigquery_table_name, project_id = \"qwiklabs-gcp-8d3d0cd07cef9252\", if_exists = \"replace\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Create SQL query\n",
    "query=\"\"\"\n",
    "SELECT\n",
    "  video_id,\n",
    "  mean_rgb,\n",
    "  mean_audio\n",
    "FROM\n",
    "  `qwiklabs-gcp-8d3d0cd07cef9252.ryan_youtube.tbl_video_level`\n",
    "LIMIT\n",
    "  3\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>video_id</th>\n",
       "      <th>mean_rgb</th>\n",
       "      <th>mean_audio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0FDy3F9Gqo</td>\n",
       "      <td>[0.5610039830207825, 0.6452203989028931, 0.365...</td>\n",
       "      <td>[-1.1589237451553345, 0.8263356685638428, 0.21...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0CK7kXtP-U</td>\n",
       "      <td>[0.18520089983940125, -0.03229318931698799, -0...</td>\n",
       "      <td>[0.4032512307167053, -0.6461716294288635, 0.08...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0QTVHnvT90</td>\n",
       "      <td>[0.5585809350013733, 0.09270916134119034, -0.2...</td>\n",
       "      <td>[-0.4419490396976471, -0.3150809705257416, 0.7...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      video_id                                           mean_rgb  \\\n",
       "0  -0FDy3F9Gqo  [0.5610039830207825, 0.6452203989028931, 0.365...   \n",
       "1  -0CK7kXtP-U  [0.18520089983940125, -0.03229318931698799, -0...   \n",
       "2  -0QTVHnvT90  [0.5585809350013733, 0.09270916134119034, -0.2...   \n",
       "\n",
       "                                          mean_audio  \n",
       "0  [-1.1589237451553345, 0.8263356685638428, 0.21...  \n",
       "1  [0.4032512307167053, -0.6461716294288635, 0.08...  \n",
       "2  [-0.4419490396976471, -0.3150809705257416, 0.7...  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Export BigQuery results to dataframe\n",
    "import google.datalab.bigquery as bq2\n",
    "df_predict = bq2.Query(query).execute().result().to_dataframe()\n",
    "df_predict.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Local prediction from local model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Format dataframe to new line delimited json strings and write out to json file\n",
    "with open('video_level.json', 'w') as outfile:\n",
    "  for idx, row in df_predict.iterrows():\n",
    "    json_string = \"{\\\"video_id\\\": \\\"\" + row[\"video_id\"] + \"\\\", \\\"mean_rgb\\\": \\\"\" + row[\"mean_rgb\"].replace(\" \",\"\").replace(\"[\",\"\").replace(\"]\",\"\") + \"\\\", \\\"mean_audio\\\": \\\"\" + row[\"mean_audio\"].replace(\" \",\"\").replace(\"[\",\"\").replace(\"]\",\"\") + \"\\\"}\"\n",
    "    outfile.write(\"%s\\n\" % json_string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CLASSES           LOGITS                                                                                                   PREDICTIONS                PROBABILITIES\n",
      "[0, 1, 4, 2, 13]  [-1.3381117582321167, -2.023491144180298, -2.0803487300872803, -2.235565185546875, -2.2626023292541504]  [1.0, 1.0, 1.0, 1.0, 1.0]  [0.20782074332237244, 0.11675848811864853, 0.11102154105901718, 0.09660188108682632, 0.09426794201135635]\n",
      "[0, 1, 4, 13, 2]  [-1.62063729763031, -2.3859150409698486, -2.425746440887451, -2.4261155128479004, -2.68080472946167]     [1.0, 1.0, 1.0, 1.0, 1.0]  [0.16511699557304382, 0.08425307273864746, 0.08123035728931427, 0.08120281249284744, 0.06411556899547577]\n",
      "[0, 1, 4, 13, 2]  [-1.658339500427246, -2.566516160964966, -2.623415231704712, -2.7371816635131836, -2.8348546028137207]   [1.0, 1.0, 1.0, 1.0, 1.0]  [0.1599850207567215, 0.07132472097873688, 0.0676465705037117, 0.06081467494368553, 0.05546950548887253]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: /usr/local/envs/py2env/lib/python2.7/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n",
      "2018-05-25 04:56:36.734122: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%bash\n",
    "model_dir=$(ls $PWD/trained_model/export/exporter | tail -1)\n",
    "gcloud ml-engine local predict \\\n",
    "    --model-dir=$PWD/trained_model/export/exporter/$model_dir \\\n",
    "    --json-instances=./video_level.json"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### GCloud ML-Engine prediction from deployed model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Format dataframe to instances list to get sent to ML-Engine\n",
    "instances = [{\"video_id\": row[\"video_id\"], \"mean_rgb\": row[\"mean_rgb\"].replace(\" \",\"\").replace(\"[\",\"\").replace(\"]\",\"\"), \"mean_audio\": row[\"mean_audio\"].replace(\" \",\"\").replace(\"[\",\"\").replace(\"]\",\"\")} for idx, row in df_predict.iterrows()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "response = {u'predictions': [{u'probabilities': [0.17853404581546783, 0.1317114382982254, 0.10703973472118378, 0.08211781829595566, 0.07856766134500504], u'logits': [-1.5263111591339111, -1.8859106302261353, -2.1213419437408447, -2.4139139652252197, -2.4619691371917725], u'classes': [0, 1, 3, 2, 4], u'predictions': [1.0, 1.0, 1.0, 1.0, 1.0]}, {u'probabilities': [0.17853404581546783, 0.1317114382982254, 0.10703973472118378, 0.08211781829595566, 0.07856766134500504], u'logits': [-1.5263111591339111, -1.8859106302261353, -2.1213419437408447, -2.4139139652252197, -2.4619691371917725], u'classes': [0, 1, 3, 2, 4], u'predictions': [1.0, 1.0, 1.0, 1.0, 1.0]}, {u'probabilities': [0.17853404581546783, 0.1317114382982254, 0.10703973472118378, 0.08211781829595566, 0.07856766134500504], u'logits': [-1.5263111591339111, -1.8859106302261353, -2.1213419437408447, -2.4139139652252197, -2.4619691371917725], u'classes': [0, 1, 3, 2, 4], u'predictions': [1.0, 1.0, 1.0, 1.0, 1.0]}]}\n"
     ]
    }
   ],
   "source": [
    "# Send instance dictionary to receive response from ML-Engine for online prediction\n",
    "from googleapiclient import discovery\n",
    "from oauth2client.client import GoogleCredentials\n",
    "import json\n",
    "\n",
    "credentials = GoogleCredentials.get_application_default()\n",
    "api = discovery.build('ml', 'v1', credentials=credentials)\n",
    "\n",
    "request_data = {\"instances\": instances}\n",
    "\n",
    "parent = 'projects/%s/models/%s/versions/%s' % (PROJECT, 'youtube_8m_video_level_datasets', 'v1')\n",
    "response = api.projects().predict(body = request_data, name = parent).execute()\n",
    "print(\"response = {}\".format(response))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
